01944nas a2200145 4500008004100000245004000041210004000081520152200121100001801643700001501661700002001676700002101696700002301717856005801740 2022 eng d00aMaking Blockchain Validators Honest0 aMaking Blockchain Validators Honest3 a

The importance of honesty among blockchain validators can not be overemphasized, especially as blockchain is used by many as an underlying technology for the development of various Industry 4.0 solutions. In the blockchain consensus process, validators validate the correctness of transactions and propose new blocks for addition to the blockchain. They are rewarded for this task with the blockchain native token (e.g., ETH on the Ethereum blockchain). This reward is often distributed among validators with respect to their staked amount. An increasing number of validators joining the network leads to a decreasing chance of a validator being chosen for the validation task and thus a reduction in the validation reward. This situation results in some form of competition among the validators, leading them to carry out various malicious actions to influence the blockchain validator selection protocol in order to be chosen. In this paper, we examine the competitive interactions between validators in a blockchain consensus process and propose a model using an infinitely repeated game model that ensures that the validators are deterred from behaving maliciously while also encouraging a self-policing notion due to the extra incentive mechanism of an improved reputation score when a validator can verifiably report malicious activities by others. Further, we discuss the factors that can incentivize or disincentivize a validator to either continue to behave honestly or switch to dishonest behavior.

1 aSalau, Abiola1 aDantu, Ram1 aMorozov, Kirill1 aBadruddoja, Syed1 aUpadhyay, Kritagya uhttps://ieeexplore.ieee.org/abstract/document/992195201784nas a2200157 4500008004100000245004500041210004500086520130700131100002101438700001501459700001501474700001901489700001801508700002301526856007701549 2022 eng d00aMaking Smart Contracts Predict and Scale0 aMaking Smart Contracts Predict and Scale3 a

The machine learning algorithms can predict the events based on the trained models and datasets. However, a reliable prediction requires the model to be trusted and tamper-resistant. Blockchain technology provides trusted output with consensus-based transactions and an immutable distributed ledger. The machine learning algorithms can be trained on blockchain smart contracts to produce trusted models for reliable prediction. But most smart contracts in the blockchain do not support floating-point data type, limiting computations for classification, which can affect the prediction accuracy. In this work, we propose a novel method to produce floating-point equivalent probability estimation to classify labels on-chain with a Naive Bayes algorithm. We derive a mathematical model with Taylor series expansion to compute the ratio of the posterior probability of classes to classify labels using integers. Moreover, we implemented our solution in Ethereum blockchain smart-contract with the Solidity programming language, where we achieved a prediction accuracy comparable to the scikit-learn library in Python. Our derived method is platform-agnostic and can be supported in any blockchain network. Furthermore, machine learning and deep-learning algorithms can borrow the derived method.

1 aBadruddoja, Syed1 aDantu, Ram1 aHe, Yanyan1 aThompson, Mark1 aSalau, Abiola1 aUpadhyay, Kritagya uhttps://nsl.cse.unt.edu/content/making-smart-contracts-predict-and-scale01764nas a2200133 4500008004100000245009400041210006900135520123700204100001901441700001501460700001901475700002101494856011501515 2022 eng d00aQuantum Networks: Reset-and-Reuse can be a Game-changer for Entanglement via Distillation0 aQuantum Networks ResetandReuse can be a Gamechanger for Entangle3 a

The future quantum network repeater is envisioned to primarily serve the role of creating entanglement between nodes and distilling those entanglements to an optimal level of performance. During our investigation, we implemented a multi-pass protocol for entanglement distillation and tested it on the IBM-Q environment, demonstrating successively improved results after multiple passes. We implemented two versions of multi-pass distillation, BBPSSW and DEJMPS, with a focus on optimizing the use of qubits, via the reset-and-reuse capability of the IBM implementation. The novel feature of reset-and-reuse can be a game-changer and can minimize the number of qubits required for large-scale applications. We also found that, though it is currently not possible to implement a criterion for continued distillation passes as a run-time feedback loop, the process can be studied through post-circuit data analysis. Our results also show that fidelity alone may guide us to discard some approaches that show success based on other metrics, such as entanglement success and success of transmitting a bit of data. The fidelity was experimentally found to be excessively low, for this complex process of multi-pass distillation.

1 aGermain, Julie1 aDantu, Ram1 aThompson, Mark1 aDockendorf, Mark uhttps://nsl.cse.unt.edu/content/quantum-networks-reset-and-reuse-can-be-game-changer-entanglement-distillation01694nas a2200169 4500008004100000245007200041210006900113520116400182653001101346653000901357653002201366653002801388100001901416700001501435700001901450856005501469 2022 eng d00aQubit Reset and Refresh: A Gamechanger for Random Number Generation0 aQubit Reset and Refresh A Gamechanger for Random Number Generati3 a

Generation of random binary numbers for cryptographic use is often addressed using pseudorandom number generating functions in compilers and specialized cryptographic packages. Using the IBM’s Qiskit reset functionality, we were able to implement a straight-forward in-line Python function that returns a list of quantum-generated random numbers, by creating and executing a circuit on IBM quantum systems. We successfully created a list of 1000 1024-bit binary random numbers as well as a list of 40,000 25-bit binary random numbers for randomness testing, using the NIST Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications. The quantum-generated random data we tested showed very strong randomness, according to the NIST suite. Previously, IBM’s quantum implementation required a single qubit for each bit of data generated in a circuit, making generation of large random numbers impractical. IBM’s addition of the reset instruction eliminates this restriction and allows for the creation of functions that can generate a larger quantity of data-bit output, using only a small number of qubits.

10aQiskit10aQRNG10aQuantum Computing10aRandom Number Generator1 aGermain, Julie1 aDantu, Ram1 aThompson, Mark uhttps://dl.acm.org/doi/abs/10.1145/3508398.351936401957nas a2200157 4500008004100000245006400041210006300105520142700168100002101595700001501616700001501631700001901646700001801665700002301683856009301706 2022 eng d00aSmarter Contracts to Predict using Deep-Learning Algorithms0 aSmarter Contracts to Predict using DeepLearning Algorithms3 a

Deep learning techniques can predict cognitive intelligence from large datasets involving complex computations with activation functions. However, the prediction output needs verification for trust and reliability. Moreover, these algorithms suffer from the model's provenance to keep track of model updates and developments. Blockchain smart contracts provide a trustable ledger with consensus-based decisions that assure integrity and verifiability. In addition, the immutability feature of blockchain also supports the provenance of data that can help deep learning algorithms. Nevertheless, smart contract languages cannot predict due to the absence of floating-point operations required by activation functions of neural networks. In this paper, we derive a novel method using the Taylor series expansion to compute the floating-point equivalent output for activation functions. We train the deep learning model off-chain using a standard Python programming language. Moreover, we store models and predict on-chain with blockchain smart contracts to produce a trusted forecast. Our experiment and analysis achieved an accuracy (99%) similar to popular Keras Python library models for the MNIST dataset. Furthermore, any blockchain platform can reproduce the activation function using our derived method. Last but not least, other deep learning algorithms can reuse the mathematical model to predict on-chain.

1 aBadruddoja, Syed1 aDantu, Ram1 aHe, Yanyan1 aThompson, Mark1 aSalau, Abiola1 aUpadhyay, Kritagya uhttps://nsl.cse.unt.edu/content/smarter-contracts-predict-using-deep-learning-algorithms01764nas a2200205 4500008004100000245007100041210006900112520107300181653001801254653002201272653002701294653002601321653001701347100001801364700001501382700002001397700002301417700002101440856009701461 2022 eng d00aTowards a Threat Model and Security Analysis for Data Cooperatives0 aTowards a Threat Model and Security Analysis for Data Cooperativ3 a

Data cooperative (called “data coop” for short) is an emerging approach in the area of secure data management. It promises its users a better protection and control of their data, as compared to the traditional way of their handling by the data collectors (such as governments, big data companies, and others). However, for the success of data coops, existing challenges with respect to data management systems need to be adequately addressed. Especially, they concern terms of security and privacy, as well as the power imbalance between providers/owners and collectors of data. Designing a security and privacy model for a data coop requires a systematic threat modeling approach that identifies the security landscape, attack vectors, threats, and vulnerabilities, as well as the respective mitigation strategies. In this paper, we analyze the security of data cooperatives, identify potential security risks and threats, and suggest adequate countermeasures. We also discuss existing challenges that hinder the widespread adoption of data coops. 

10aCybersecurity10aData Cooperatives10aSecure Data Management10aSecurity and Privacy.10aThreat Model1 aSalau, Abiola1 aDantu, Ram1 aMorozov, Kirill1 aUpadhyay, Kritagya1 aBadruddoja, Syed uhttps://nsl.cse.unt.edu/content/towards-threat-model-and-security-analysis-data-cooperatives01752nas a2200157 4500008004100000245005200041210005200093520126200145100002101407700001501428700001501443700001901458700001801477700002301495856007601518 2022 eng d00aTrusted AI with Blockchain to Empower Metaverse0 aTrusted AI with Blockchain to Empower Metaverse3 a

The digital experience emerging in the virtual world is a reality with the advent of the metaverse. Augmented reality(AR), virtual reality(VR), extended reality(XR), and artificial intelligence(AI) algorithms would pave the way for an immersive experience for the users in the virtual space. However, the explosion of these technologies broaches new challenges to threaten the success of metaverse due to security risks. The blockchain technology augmented with AI promises to deliver a trusted metaverse for everyone. Nevertheless, smart contracts fail to produce a cognitive prediction, dissuading users from confiding in the metaverse. We arm smart contracts with intelligence to predict using AI algorithms. Moreover, we deploy the smart contracts on the Ethereum blockchain platform and produce a prediction accuracy of 95% compared to Python scikit-learn-based predictions. Our results show that the prediction delay can obstruct the growth of metaverse applications to accept blockchain technologies. Furthermore, the limitation of blockchain technology can make integration unreasonable. Therefore, we discuss possible scalability solutions that can be part of our future work to help more metaverse applications adopt blockchain solutions.

1 aBadruddoja, Syed1 aDantu, Ram1 aHe, Yanyan1 aThompson, Mark1 aSalau, Abiola1 aUpadhyay, Kritagya uhttps://nsl.cse.unt.edu/content/trusted-ai-blockchain-empower-metaverse02775nas a2200313 4500008004100000020002200041245005000063210004800113260002700161520191300188653001402101653002002115653001502135653001202150653001502162653001302177653002002190653002102210653002802231653000802259653001902267653002502286100002302311700001502334700001502349700002102364700001802385856005802403 2021 eng d a978-1-6654-1623-800aCan't Understand SLAs? Use the Smart Contract0 aCant Understand SLAs Use the Smart Contract aAtlanta, GA, USAbIEEE3 a

A Service Level Agreement (SLA) is a special kind of legal contract that binds a vendor to its customers where the vendor commits to provide certain services in exchange for certain payment from the customers. On the other hand, a Smart Contract is a contract that is a computer program that also binds multiple parties into given agreements but is a set of a precise rules and is self-enforceable and self-executable. Since almost all legal contracts are ambiguous by nature and are complex to read and understand, we perform a novel study on how we can replace the traditional vague legal contract with the smart contact and the effect of the ambiguity on the smart contract by performing a thorough analysis on SLAs by measuring their ambiguities in various aspects. We take several samples of real SLAs from six different popular broadband vendors. We use four random SLAs to train the machine learning model to classify and then detect ambiguous words in two unseen SLAs which were the SLAs of Ziply Fiber and Century Link. As different people form different interpretations while reading the ambiguous legal contracts, we generate various human interpretations from the machine detected ambiguous words and convert all those generated interpretations into Smart Contracts to perform testing in Ethereum-based Blockchain to identify the most ambiguous as well as accurate interpretation of the SLA. From our analysis and observation, we were able to find out the most ambiguous interpretation of SLAs and we concluded that the SLA of Ziply Fiber was more ambiguous in general compared to the SLA of Century Link. Moreover, our proposed approach to detect ambiguous terms and to translate an ambiguous legal contract to a smart legal contract using a formal language to measure the degree of ambiguity can be extrapolated and replicated to legal contracts from other types of industries as well.

10aambiguity10aambiguity index10ablockchain10aclauses10acomplexity10aEthereum10ainterpretations10amachine learning10aservice level agreement10aSLA10asmart contract10asmart legal contract1 aUpadhyay, Kritagya1 aDantu, Ram1 aHe, Yanyan1 aBadruddoja, Syed1 aSalau, Abiola uhttps://ieeexplore.ieee.org/abstract/document/975025001909nas a2200205 4500008004100000020002200041245007200063210006900135260002700204520122500231653003301456653003101489653002001520653002701540100002201567700002001589700001501609700002101624856005801645 2021 eng d a978-1-6654-1625-200aA Collaborative and Adaptive Feedback System for Physical Exercises0 aCollaborative and Adaptive Feedback System for Physical Exercise aAtlanta, GA, USAbIEEE3 a

Maintaining motivation to meet physical exercise goals is a big challenge in virtual/home-based exercise guidance systems. Lack of motivation, long-maintained bad daily routines, and fear of injury are some of the reasons that cause this hesitation. This paper proposes a reinforcement learning-based virtual exercise assistant capable of providing encouragement and customized feedback on body movement form over time. Repeated arm curls were observed and tracked using single and dual-camera systems using the Posenet pose estimation library. To accumulate enough experience across individuals, the reinforcement learning model was collaboratively trained by subjects. The proposed system is tested on 36 subjects. Behavioral changes are apparent in 31 of the 36 subjects, with 31 subjects reducing movement errors over time and 15 subjects completely eliminating the errors. The system was analyzed for which types of feedback provided the highest expected value, and feedback directly related to the previous mistake provided the highest valued feedback ( p<0.0133 ). The result showed that the Reinforcement Learning system provides meaningful feedback and positively impacts behavior progress.

10aDistributed Machine Learning10aHuman-Computer Interaction10aPose Estimation10aReinforcement Learning1 aRanasinghe, Ishan1 aYuan, Chengping1 aDantu, Ram1 aAlbert, Mark, V. uhttps://ieeexplore.ieee.org/abstract/document/970716601611nas a2200229 4500008004100000020002200041245005200063210005000115260002700165520092100192653001801113653003101131653002401162653002001186653002701206100002201233700001501255700002101270700001501291700001701306856005801323 2021 eng d a978-3-903176-32-400aCyber-Physiotherapy: Rehabilitation to Training0 aCyberPhysiotherapy Rehabilitation to Training aBordeaux, FrancebIEEE3 a

Cutting-edge Human-Computer Interaction (HCI) technologies embedded with Machine Learning (ML) will cause a paradigm shift in various domains, including manufacturing and developing facilities and services for professional and personal use. ML implemented HCIs can help people overcome societal challenges brought about by the COVID-19 pandemic. We introduce a system for people to perform physical exercises at home. This system is intended to help a range of demographics, from non-critical physical therapy patients to experienced weightlifters. More specifically, we propose a method to assess the difficulty of an exercise for visual exercise tracking systems. Pose estimation tracks exercises and reinforcement learning provides autonomous feedback to the user (patient/athlete). This information is processed largely on the client side, allowing the application to run smoothly anywhere in the world.

10aFitts’s law10aHuman-Computer Interaction10aIndex of Difficulty10aPose Estimation10aReinforcement Learning1 aRanasinghe, Ishan1 aDantu, Ram1 aAlbert, Mark, V.1 aWatts, Sam1 aOcana, Ruben uhttps://ieeexplore.ieee.org/abstract/document/946403602158nas a2200241 4500008004100000020002200041245004500063210004500108260002800153520147700181653001501658653001801673653002101691653001701712653002301729653001801752653001301770653001901783100001801802700001501820700002301835856005801858 2021 eng d a978-1-6654-3578-900aData Cooperatives for Neighborhood Watch0 aData Cooperatives for Neighborhood Watch aSydney, AustraliabIEEE3 a

The increasing proliferation of user data is moving the world from the era of 'big data' to a new era of shared data, and some are considering data as a factor of production that is paving the way for a new business economy. In this paper, we propose a solution that uses blockchain technology as a platform for online neighborhood watch using a form of data cooperative among individuals or organizations in the sharing of data through a peer-to-peer mechanism. We prove the concept by implementing a distributed phishing data sharing system that will maintain a community ledger of reported phishing activities with a consensus-based approval of the phishing transaction and a novel reputation scoring system thereby adding reliability to the system and effectively tackling the phishing problem. The data cooperative provides a way for timely multi-party sharing of phishing data among anti-phishing organizations and users of the internet eliminating the current approach of each organization maintaining its database. Our results show that blockchain is effective in complementing the existing methods of phishing detection and serves as a platform for sharing phishing data with respect to scalability, cost, and memory consumption. Also, our results further show that transaction times on the Ropsten test net follow a Gamma distribution. Our approach can be extrapolated to other data sharing systems like medical data, spam calls, discussion forums, etc.

10ablockchain10aCybersecurity10adata cooperative10adata sharing10adistributed ledger10apeer-to- peer10aphishing10asmart contract1 aSalau, Abiola1 aDantu, Ram1 aUpadhyay, Kritagya uhttps://ieeexplore.ieee.org/abstract/document/946105602393nas a2200301 4500008004100000020002200041245007000063210006900133260002700202520152700229653001401756653001501770653001201785653001501797653001301812653001601825653002001841653002801861653000801889653001901897653002501916100002301941700001501964700001501979700001801994700002102012856005802033 2021 eng d a978-1-6654-1623-800aMake Consumers Happy by Defuzzifying the Service Level Agreements0 aMake Consumers Happy by Defuzzifying the Service Level Agreement aAtlanta, GA, USAbIEEE3 a

A Service Level Agreement (SLA) is a special kind of legal contract that binds a vendor to its customers where the vendor commits to provide certain services in exchange for certain payments from the customers. However, when customers do not get the services that they have subscribed for, it becomes a laborious job for customers to contact or visit the company and claim the correct amount of compensation or service credits. On the other hand, a Smart Contract is a contract that is a computer program that also binds multiple parties into given agreements but is a set of precise rules and is self-enforceable and self-executable. In this paper, we have introduced a novel work where we use fuzzy logic inside the Ethereum-based smart contract for two significant objectives. The first objective is to make the claim of the compensation easier and faster for customers by translating the SLA into a smart contract. The second objective is to make the smart contract even smarter and intelligent by implementing fuzzy logic so that customers who have a hard time understanding the legal jargon and ambiguities of the legal contract and SLA to find out if the compensation amount they are getting when the service is poor is good enough. Since fuzzy logic models semantics of linguistic expressions by capturing vagueness in the fuzzy sets, it becomes easier to solve the problem of contractual ambiguities and expedite the process of claiming compensation when implemented in a Blockchain-based smart contract.

10aambiguity10ablockchain10aclauses10acomplexity10aEthereum10aFuzzy logic10ainterpretations10aservice level agreement10aSLA10asmart contract10asmart legal contract1 aUpadhyay, Kritagya1 aDantu, Ram1 aHe, Yanyan1 aSalau, Abiola1 aBadruddoja, Syed uhttps://ieeexplore.ieee.org/abstract/document/975025801646nas a2200241 4500008004100000020002200041245003500063210003500098260002800133520098300161653002801144653001501172653000901187653002101196653001601217653001901233100002101252700001501273700001501288700002401303700001901327856005801346 2021 eng d a978-1-6654-3578-900aMaking Smart Contracts Smarter0 aMaking Smart Contracts Smarter aSydney, AustraliabIEEE3 a

Blockchain technology develops static smart contracts for decentralized business transactions, lacks dynamic decision-making capabilities that limit the possibilities of ever-increasing demands of modern business applications. Artificial intelligence, a computational prediction platform provides intelligent predictions, actions, and recognition that lacks the ability to hold on to the integrity of the prediction result and requires the help of external authorities to secure the system. Blockchain-based AI prediction can cover the gaps of individual technologies and can mutually benefit from one another to develop a decentralized machine learning architecture that promises to yield better security, automation, and dynamism of the application. This paper proposes a Naive Bayes prediction algorithm to perform prediction with inside blockchain smart contracts that promises to open up more opportunities in the field of Blockchain-AI decentralized applications.

10aartificial intelligence10ablockchain10aDApp10amachine learning10aNaive Bayes10asmart contract1 aBadruddoja, Syed1 aDantu, Ram1 aHe, Yanyan1 aUpadhayay, Kritagya1 aThompson, Mark uhttps://ieeexplore.ieee.org/abstract/document/946114802028nas a2200277 4500008004100000020002200041245005900063210005900122260002700181520120900208653001401417653002801431653001501459653002401474653001901498653001301517653002001530653001901550653003101569100002301600700001501623700001501638700001801653700002101671856005801692 2021 eng d a978-1-6654-1623-800aParadigm Shift from Paper Contracts to Smart Contracts0 aParadigm Shift from Paper Contracts to Smart Contracts aAtlanta, GA, USAbIEEE3 a

The ambiguity and complexity of the traditional legal contracts have motivated the study and exploration of a better and advanced contract known as blockchain-based smart contracts. A smart contract is a self-executable contract where the terms of the agreement between the involved parties are directly written into the lines of code that resides in the distributed ledger technology known as the blockchain. Obtaining a better understanding of smart contracts to overcome the fundamental issues of traditional legal contracts is vital for the successful and faster dispute settlement process without the intervention of any third-party mediators like courts, banks, lawyers, etc. In this paper, we present a comprehensive overview of the key features of the paradigm shift from traditional paper contracts to smart contracts. In addition, we also discuss why smart contracts are necessary to be legally enforced and the crucial conditions that are required for them to be legally enforceable. Furthermore, we outline recent trends and emerging technologies such as Natural Language Processing, Machine Learning, and the Internet of Things that have been combined together with smart contracts.

10aambiguity10aartificial intelligence10ablockchain10aelectronic contract10aenforceability10aEthereum10ainterpretations10asmart contract10atraditional legal contract1 aUpadhyay, Kritagya1 aDantu, Ram1 aHe, Yanyan1 aSalau, Abiola1 aBadruddoja, Syed uhttps://ieeexplore.ieee.org/abstract/document/975022601237nas a2200133 4500008004100000245006000041210006000101520077200161100002300933700001500956700002100971700001900992856009201011 2020 eng d00aAdaptive and Predictive SDN Control During DDoS Attacks0 aAdaptive and Predictive SDN Control During DDoS Attacks3 a

While Distributed Denial of Service (DDoS) attacks continue to plague the Internet, Software Defined Networks (SDNs) offer the promise of configuration elasticity for all devices in the plant to mitigate these attacks and stabilize the network in real-time. Since it is difficult to distinguish between legitimate and attack traffic, we propose a closed-loop feedback control mechanism using a multi-loop proportional, integral (PI) controller and a model predictive controller (MPC) that will regulate the system characteristics with disturbance rejection. Results from our setup implemented in the SDN platform show that our dynamic and predictive control models provide for a graceful degradation of real-time services in the SDN environment in real-time.

1 aVempati, Jagannadh1 aDantu, Ram1 aBadruddoja, Syed1 aThompson, Mark uhttps://nsl.cse.unt.edu/content/adaptive-and-predictive-sdn-control-during-ddos-attacks02071nas a2200253 4500008004100000020002200041245006800063210006800131260003100199520130700230653001501537653001801552653002001570653002301590653001901613653000801632653002001640100002101660700001501681700001801696700002201714700002301736856005801759 2020 eng d a978-1-7281-7445-700aIntegrating DOTS With Blockchain Can Secure Massive IoT Sensors0 aIntegrating DOTS With Blockchain Can Secure Massive IoT Sensors aNew Orleans, LA, USAbIEEE3 a

This paper presents a novel approach to securing IoT devices by leveraging DDoS Open Threat Signaling (DOTS) architecture on a Blockchain framework. Like many areas of the information technology domain, IoT sensors are also prone to attacks but on a larger scale. There are millions of devices being connected to a central domain to provide different types of services. Since these low-powered IoT devices have constrained technical requirements with less computational capabilities, they lack the capacity to judge their behavior as benign or malignant. IoT relies heavily on the higher level of intelligent nodes to decide on their status. An IoT Controller/Edge server handles the registration and the limited management of devices. Since traditional security is unable to protect the IoT environment sufficiently, we present a Blockchain-based DDoS detection approach to secure and mitigate such attacks in the IoT environment. Our test setup includes dataset from four sensors over two months. These values were tested using a threshold calculation against the variation of temperature, humidity, pressure, and wind direction on that day to find out whether an IoT sensor is under a DDoS attack. Our results show how DOTS can help in detection of attack when mapped on IoT edge computing.

10ablockchain10aCybersecurity10aDDOS Protection10adistributed ledger10aEdge Computing10aIoT10aSmart Contracts1 aBadruddoja, Syed1 aDantu, Ram1 aWidick, Logan1 aZaccagni, Zachary1 aUpadhyay, Kritagya uhttps://ieeexplore.ieee.org/abstract/document/915034501594nas a2200145 4500008004100000245007200041210006800113260000900181520108200190100002301272700001501295700002201310700002101332856009501353 2020 eng d00aIs your legal contract ambiguous? Convert to a smart legal contract0 ayour legal contract ambiguous Convert to a smart legal contract bIEEE3 a

A legal contract is something that is in spoken or in written form, which binds a party or multiple parties into given terms and conditions. On the other hand, a smart contract is also a contract which is a computer program that binds parties into given terms and conditions but unlike a legal contract, it is self-executable, efficient, and unambiguous. Almost all legal contracts are complex while reading because of its ambiguous nature. In this paper, we take a real-world ambiguous legal contact as a test contract, and generate various interpretations from it, convert all those interpretations into the smart legal contracts and identify the most ambiguous and accurate smart legal contract by performing various measurements such as transaction fees and ambiguity index for each interpretation. We came to the conclusion that the most ambiguous legal contract would be the contract with general interpretation as it was more complex when written in the smart contract and had many possible interpretations due to ambiguity than the rest of the interpretations.

1 aUpadhyay, Kritagya1 aDantu, Ram1 aZaccagni, Zachary1 aBadruddoja, Syed uhttps://nsl.cse.unt.edu/content/your-legal-contract-ambiguous-convert-smart-legal-contract01424nas a2200229 4500008004100000245009700041210006900138260000900207520065400216653001900870653001800889653001500907653002400922653000800946653002500954653001300979100001800992700002201010700001501032700002201047856012501069 2019 eng d00aBlockchain Based Authentication and Authorization Framework for Remote Collaboration Systems0 aBlockchain Based Authentication and Authorization Framework for  cJune3 a

Due to the advantages of blockchain technologies, including decentralization, immutability, transparency and security, people try to replace existing problematic architectures /frameworks with blockchain based ones. In this paper we propose a novel authentication and authorization framework based on blockchain technologies to control access to the resources of an IoT device. In this paper, we focus on devices such as the Cyber Handyman used in remote collaboration applications to develop our framework. We tested our smart contracts on the Ropsten test network. Our results showed that it can handle 25 service requests simultaneously.

10aAccess Control10aauthorization10ablockchain10aDigital Certificate10aIoT10aremote collaboration10aSecurity1 aWidick, Logan1 aRanasinghe, Ishan1 aDantu, Ram1 aJonnada, Srikanth uhttps://nsl.cse.unt.edu/content/blockchain-based-authentication-and-authorization-framework-remote-collaboration-systems00634nas a2200193 4500008004100000020002200041245005900063210005800122260002700180653002800207653002400235653002900259653002500288653002400313100002100337700001500358700002000373856004700393 2019 eng d a978-1-4503-6753-000aCMCAP: Ephemeral Sandboxes for Adaptive Access Control0 aCMCAP Ephemeral Sandboxes for Adaptive Access Control aNew York, NY, USAbACM10aadaptive access control10aephemeral sandboxes10ainformation flow control10aintrusion prevention10aruntime containment1 aBucuti, Theogene1 aDantu, Ram1 aMorozov, Kirill uhttp://doi.acm.org/10.1145/3322431.332541400408nas a2200121 4500008004100000245006900041210006800110490001900178100001800197700002000215700001500235856003600250 2019 eng d00aDetecting driver distraction using stimuli-response EEG analysis0 aDetecting driver distraction using stimuliresponse EEG analysis0 vabs/1904.091001 aBajwa, Garima1 aFazeen, Mohamed1 aDantu, Ram uhttp://arxiv.org/abs/1904.0910002391nas a2200193 4500008004100000245004400041210004300085260000900128520184600137653001501983653001701998653001402015653001902029653001902048100002502067700001502092700001902107856007102126 2019 eng d00aDistributed Ledger for Spammers' Resume0 aDistributed Ledger for Spammers Resume cJune3 a

Unsolicited, and most likely spoofed, robot calls are not just an annoyance, but also carry a potential threat with the onset of automation, impersonation, and even voice manipulation technologies as malicious elements attempt to use deception to steal sensitive information or invoke action. Despite steps taken to protect consumers, the issue appears to be far from under control. In this paper, we propose a solution to use blockchain as a platform to share spam transactions through a peer-to-peer mechanism that will maintain a global database of reported spam transactions in order to identify and trace spam activity effectively. Storing spam transactions on a distributed ledger with consensus-based approval of transactions adds reliability to the data and can optimize the data points that will be available to spam detection algorithms in order to fight spam effectively. As this is peer to peer-based sharing, there is no need to rely on third-party providers for storing and sharing this data to the users. Every spam call received will be added as a detailed transaction on the blockchain to execute a smart contract that will calculate the trustworthiness of the caller. Call records are used to identify spam transactions while the blockchain ledgers store this data. We discuss the relevance and advantages of a distributed ledger to store these transactions. This paper does not aim at solving the spam problem with an optimized detection algorithm but evaluates the characteristics and performance of the blockchain as a distributed ledger and its relevance to serve as a platform for peer-to-peer spam detection mechanisms. We evaluate different blockchain metrics like transaction processing rates, gas costs and ledger sizes and discuss how they scale in order to store the spam reports data on the blockchain.

10ablockchain10aPeer-to-peer10aRobocalls10asmart contract10aSpam detection1 aMuttavarapu, Anudeep1 aDantu, Ram1 aThompson, Mark uhttps://nsl.cse.unt.edu/content/distributed-ledger-spammers-resume01304nas a2200121 4500008004100000245005900041210005700100520088400157100002201041700001701063700001501080856008701095 2019 eng d00aMicro-Accreditation for Matching Employer E-Hire Needs0 aMicroAccreditation for Matching Employer EHire Needs3 a

This paper presents a novel way to help match employers' knowledge requirements with students' knowledge earned using blockchain's smart contracts to assure credentials and track student records. This decentralized approach proposes using the micro-accreditation of topics from the CAE framework to courses and associated tasks, while introducing a revolutionary idea of a blockchain-based peer-reviewed rigor score assignment. Our work and result metrics were completed in Ethereum and connected test networks. We concluded this new approach is mostly efficient and scalable depending on the network load, with faster transaction times when the miners are properly incentivized. Future work will include further fine-tuning of the transaction algorithms to improve time, as well as an investigation into a better consensus model for peer review and rigor determination.

1 aZaccagni, Zachary1 aPaul, Aditya1 aDantu, Ram uhttps://nsl.cse.unt.edu/content/micro-accreditation-matching-employer-e-hire-needs01450nas a2200205 4500008004100000020001800041245007100059210006900130260005900199520080700258653001201065653001801077653001801095653002101113653001001134100002101144700001501165700002001180856004401200 2019 eng d a978145036753000aVerifying OAuth Implementations Through Encrypted Network Analysis0 aVerifying OAuth Implementations Through Encrypted Network Analys aNew York, NY, USAbAssociation for Computing Machinery3 a

Verifying protocol implementations via application analysis can be cumbersome. Rapid development cycles of both the protocol and applications that use it can hinder up-to-date analysis. A better approach is to use formal models to characterize the applications platform and then verify the protocol through analysis of the network traffic tied to the models. To test this method, the popular protocol OAuth is considered. Currently, formal models of OAuth do not take into consideration the mobile environment, and implementation verification is largely based on code analysis. Our preliminary results are two fold; we sketch an extension to a formal model that incorporates the specifics of the Android platform and classify OAuth device types using machine learning on encrypted VPN traffic.

10aAndroid10aauthorization10aformal models10anetwork analysis10aoauth1 aTalkington, Josh1 aDantu, Ram1 aMorozov, Kirill uhttps://doi.org/10.1145/3322431.332644903105nas a2200505 4500008004100000245010300041210006900144260000800213520152300221653001801744653003101762653002401793653003901817653001901856653003201875653003001907653000901937653004201946653002101988653002502009653001302034653002302047653002002070653001602090653001502106653003702121653000802158653000802166653002602174653002302200653002302223653002202246653002202268653001402290653002902304653002002333653000802353653001602361653002002377653002602397653002302423100002302446700001502469856011502484 2018 eng d00aAutomatic Feedback Control for Graceful Degradation of Real-Time Services in the Face of an Attack0 aAutomatic Feedback Control for Graceful Degradation of RealTime  cOct3 a

Distributed denial of service (DDoS) attacks continue to pose a serious threat to various businesses and consumers. With the growth in the number of devices connected to the internet, these attacks continue to grow in number. Despite the availability of security tools, the attacks continue to happen and are causing various businesses to sweat. These tools may take anywhere from a few hours to a few days to counter the attacks, which is unacceptable. In this paper, we put forth a novel feedback control mechanism to minimize the effect of volumetric attacks such as DDoS. During an attack, the feedback control model detects and reduces the impact of the attack by maintaining the service level agreements (SLA) of the network service. The controller makes intelligent decisions to ensure the quality of service (QoS) metrics are gracefully degraded by tuning the micro-firewall rules such as the committed information rate and burst size. A proportional Integral (PI) controller is used as a closed-loop feedback controller to maintain the stability of the network in spite of an attack. This proposed architecture is verified in a lab setup, and we observe that we are able to minimize the degradation of the real-time service so that the user's quality of experience (QoE) is preserved. We validate the proposed architecture with a model generated by using the system identification technique. Results from the setup show that the closed-loop feedback control model stabilizes the network in real-time.

10aauthorisation10aautomatic feedback control10aclosed loop systems10aclosed-loop feedback control model10aComputer crime10acomputer network management10acomputer network security10aDDoS10aDistributed Denial of Service attacks10afeedback control10aGraceful Degradation10aInternet10aMathematical model10anetwork service10aPacket loss10aPI control10aproportional Integral controller10aQoE10aQoS10aquality of experience10aquality of service10aReal Time Services10areal-time service10areal-time systems10aResilient10aservice level agreements10aservice metrics10aSLA10astate space10aStreaming media10aSystem Identification10avolumetric attacks1 aVempati, Jagannadh1 aDantu, Ram uhttps://nsl.cse.unt.edu/content/automatic-feedback-control-graceful-degradation-real-time-services-face-attack00416nas a2200097 4500008004100000245007700041210006900118100001900187700001500206856009700221 2018 eng d00aBridging the Gap: Developing Innovative Minds Early On for Cybersecurity0 aBridging the Gap Developing Innovative Minds Early On for Cybers1 aThompson, Mark1 aDantu, Ram uhttps://nsl.cse.unt.edu/content/bridging-gap-developing-innovative-minds-early-cybersecurity02519nas a2200313 4500008004100000245007700041210006900118260000800187520151400195653001801709653002501727653002101752653002201773653001201795653001401807653003201821653003001853653003201883653003101915653001401946653002501960653002001985653001802005653001802023100002202041700001502063700002202078856010502100 2018 eng d00aCyber Handyman and Nursing for Humanitarian Services and Disaster Relief0 aCyber Handyman and Nursing for Humanitarian Services and Disaste cOct3 a

Calamities cause immense damage to the lives and properties; emergency management and humanitarian support have always been a challenge in the disaster-hit areas due to deficiency of skilled workforce and increase in demand for available experts. Not all the volunteers have the required technical expertise to handle those situations, utilizing the services of the remotely located experts to enhance the skills of the volunteers can help them to handle the situations efficiently. The existing communication mechanisms do not have the capabilities required for collaborating people over physical tasks, which is crucial during the emergency situations. In this paper, we present two novel remote collaboration systems, Cyber-Handyman and Cyber-Nurse using which the less-trained and inexperienced aid workers can enhance their capabilities with the help from remote experts. These units will be deployed in the disaster sites, and the remote experts access and control the sensors on it to guide the aid workers or the victims. The efficiency of the collaboration over physical tasks, which is vital during emergency situations, depends on the complexity of the protocols utilized and the efficiency of the collaboration system. We also propose a methodology to evaluate the protocol complexity and efficiency of the system. Our experiments and results show that with our collaboration system a remote helper can successfully guide the workers in performing a physical task with minimum difficulty.

10aCollaboration10acollaboration system10acommon grounding10aComplexity theory10aEntropy10aGrounding10ahelper-worker collaboration10ahuman-human collaboration10ahuman-machine collaboration10aprotocol complexity theory10aProtocols10aremote collaboration10aSenior citizens10aTask analysis10avoice over IP1 aJonnada, Srikanth1 aDantu, Ram1 aRanasinghe, Ishan uhttps://nsl.cse.unt.edu/content/cyber-handyman-and-nursing-humanitarian-services-and-disaster-relief03445nas a2200577 4500008004100000245007100041210006900112260004100181520168900222653000801911653003501919653002501954653002801979653001502007653003602022653002102058653002802079653001802107653001902125653001802144653004202162653001502204653000902219653002402228653001302252653003302265653002102298653002802319653001302347653001802360653002202378653001302400653001602413653001602429653003102445653001902476653002702495653002502522653002102547653001902568653003402587653001402621653002002635653001802655100003102673700001502704700001702719700001702736700002002753856009402773 2018 eng d00aA Decentralized Marketplace Application on the Ethereum Blockchain0 aDecentralized Marketplace Application on the Ethereum Blockchain aPhiladelphia, PA, USAbIEEEc10/20183 a

Modern centralized online marketplaces such as eBay offer an alternative option for consumers to both sell and purchase goods with relative ease. However, drawbacks to these marketplaces include the platform's ability to block merchants at their own whim, the fees paid to the platform when listing a product and when selling a product, and the lack of privacy of users' data. In this paper, we propose an application that remedies all three of these drawbacks through use of the Ethereum blockchain platform. The application was developed using the Truffle development framework. The application's functions were contained within an Ethereum smart contract, which was then migrated to the Ethereum network. The user's input was read through a web interface and sent to the Ethereum network via the web3.js API. Statistics about the application were gathered on the Rinkeby test network. The application was shown to have an average transaction runtime of 3.8 seconds, and an average gas consumption of 4.6 wei. Contract creation times for the application were shown to be less than a second. A cost analysis of the application was then conducted. The gas consumption of the transactions needed to both buy and sell a product was converted into US dollars, and the gas cost of the application was then compared to the cost to use an online auction marketplace such as eBay as well as an in-person auction house such as Sotheby's. The results showed that selling on the application is cheaper than existing online options as well as existing in-person options. These tests showed that our application was successful in addressing the drawbacks of current auction marketplaces.

10aAPI10aapplication program interfaces10aauction marketplaces10aaverage gas consumption10ablockchain10acentralized online marketplaces10aComputer science10acontract creation times10acost analysis10aCryptocurrency10adecentralized10adecentralized marketplace application10ae-commerce10aeBay10aelectronic commerce10aEthereum10aEthereum blockchain platform10aEthereum network10aEthereum smart contract10agas cost10ahuman factors10ain-person options10aInternet10amarketplace10aMeasurement10aonline auction marketplace10aonline options10apeer-to-peer computing10aRinkeby test network10asecurity of data10asmart contract10aTruffle development framework10auser data10auser interfaces10aWeb interface1 aRanganthan, Vishnu, Prasad1 aDantu, Ram1 aPaul, Aditya1 aMears, Paula1 aMorozov, Kirill uhttps://nsl.cse.unt.edu/content/decentralized-marketplace-application-ethereum-blockchain00380nas a2200109 4500008003900000245005400039210005300093100001600146700001600162700001500178856007700193 2018 d00aEmerging Technologies Workshop I: The Case for AI0 aEmerging Technologies Workshop I The Case for AI1 aHurd, Bryan1 aDavis, Jeff1 aDantu, Ram uhttps://nsl.cse.unt.edu/content/emerging-technologies-workshop-i-case-ai00415nas a2200121 4500008003900000245005700039210005100096100001600147700001900163700001600182700001500198856008000213 2018 d00aThe Future is Connected: How Can it be Cyber Secure?0 aFuture is Connected How Can it be Cyber Secure1 aDavis, Jeff1 aKhalfan, Shaun1 aTiene, Rick1 aDantu, Ram uhttps://nsl.cse.unt.edu/content/future-connected-how-can-it-be-cyber-secure02039nas a2200229 4500008004100000022001400041245008400055210006900139300001400208490000700222520132800229653002401557100002401581700001501605700002401620700002001644700001901664700002301683700001501706700001601721856007201737 2018 eng d a1746-809400aA novel heart-mobile interface for detection and classification of heart sounds0 anovel heartmobile interface for detection and classification of  a313 - 3240 v453 a

Abstract Diagnosis of heart disease requires that a medical practitioner investigate heart auscultations for irregular sounds, followed by echocardiography and electrocardiography tests. These expensive tests also require specialized technicians to operate. We present a low-cost, patient-centered device for the initial screening of the heart sounds that can be potentially used by the users on themselves. They can later share these readings with their healthcare providers. We have created an innovative mobile-health service platform for analyzing and classifying heart sounds. The presented system enables remote patient-monitoring by integrating advanced wireless communications with a customized low-cost stethoscope. This system also permits remote management of a patient’s cardiac status while maximizing patient mobility. The smartphone application facilitates recording, processing, visualizing, listening to, and classification of heart sounds. We build our classification model using the Mel-Frequency Cepstral Coefficient and Hidden Markov Model. This application is tested in a hospital environment to collect live recordings from patients with positive results. The smartphone application correctly detected 92.68% of abnormal heart conditions in clinical trials at \{UT\} Southwestern Hospital.

10aHidden Markov Model1 aThiyagaraja, Shanti1 aDantu, Ram1 aShrestha, Pradhumna1 aChitnis, Anurag1 aThompson, Mark1 aAnumandla, Pruthvi1 aSarma, Tom1 aDantu, Siva uhttps://www.sciencedirect.com/science/article/pii/S174680941830110102146nas a2200157 4500008004100000245009400041210006900135260003800204520152900242100002201771700001501793700002401808700002201832700001801854856011601872 2018 eng d00aAn OAuth-Based Authorization Framework for Access Control in Remote Collaboration Systems0 aOAuthBased Authorization Framework for Access Control in Remote  aHuntsville, Alabama, USAc06/20183 a

Advanced human computer interaction systems have made it possible for helpers (professionals) to remotely collaborate with workers (individuals seeking assistance from the professionals). For example, a professional can remotely help a worker fix automobiles or electronics, identify how much of what medication to take, or perform household repairs. We have presented a system, Collaborative Appliance for Remote-help (CARE) that allows for such collaborations. Our system allows a skilled professional or other helper to remotely access and control a worker’s locally deployed resources over the Internet. These locally deployed resources may include cameras, microphones, speakers, processors, and memory. The remote helper then directs the worker to perform specific tasks to complete the job at hand. Like other Internet of Things (IoT) based systems, CARE is inputconstrained. That is, a worker cannot provide input via a touch screen or keyboard.

The resources are accessed over the Internet. Thus, security and privacy are big concerns. In this paper, we present the authorization and access control framework for the inputconstrained CARE system. This framework has been implemented using the OAuth 2.0 Authorization Framework and has been designed to meet the needs of resource owners who have no technical knowledge. We have shown that our proposed framework is very effective and consistent with the access control guidelines set by the National Institute of Standards and Technology (NIST).

1 aJonnada, Srikanth1 aDantu, Ram1 aShrestha, Pradhumna1 aRanasinghe, Ishan1 aWidick, Logan uhttps://nsl.cse.unt.edu/content/oauth-based-authorization-framework-access-control-remote-collaboration-systems01390nas a2200253 4500008004100000245007500041210006900116260000900185520060500194653001100799653000800810653003200818653001500850653001100865653002200876653003000898653001300928653002000941100001800961700001500979700002300994700001901017856010001036 2018 eng d00aPerformance Analysis of Elliptic Curves for Real-Time Video Encryption0 aPerformance Analysis of Elliptic Curves for RealTime Video Encry cJune3 a

The use of real-time video streaming is increasing day-by-day, and its security has become a serious issue now. Video encryption is a challenging task because of its large frame size. Video encryption can be done with symmetric key as well as asymmetric key encryption. Among different asymmetric key encryption technique, ECC performs better than other algorithms like RSA in terms of smaller key size and faster encryption and decryption operation. In this work, we have analyzed the performance of 18 different ECC curves and suggested some suitable curves for real-time video encryption.

10aDelays10aECC10aElliptic curve cryptography10aencryption10aJitter10areal-time systems10aReal-time video streaming10aSecurity10aStreaming media1 aSen, Nilanjan1 aDantu, Ram1 aVempati, Jagannadh1 aThompson, Mark uhttps://nsl.cse.unt.edu/content/performance-analysis-elliptic-curves-real-time-video-encryption02662nas a2200361 4500008004100000245010200041210006900143260000800212520147000220653003901690653001401729653000801743653001601751653002601767653002701793653002301820653001801843653001001861653002701871653003101898653002901929653001301958653002101971653003101992653001802023653001802041653004302059653001802102100001902120700001902139700001502158856012702173 2018 eng d00aPrediction of human error using eye movements patterns for unintentional insider threat detection0 aPrediction of human error using eye movements patterns for unint cJan3 a

Threats from the inside of an organization's perimeters are a significant problem since it is difficult to distinguish them from benign activities. Recent reports indicate that the accidental/unintentional incidents account for the majority ofall insider security incidents. Human error is a major factor in unintentional insider threat. In this paper, we propose a novel approach for unintentional insider threat (UIT) detection and mitigation based on eye movement patterns. We perform experiments to capture unique characteristics of a user's eye movements as they perform several computer-based activities in different scenarios. The goal is to evaluate the effectiveness of using eye movement patterns in determining a user's subjective mental workload which is one of the main contributing factors to human error. We extract eye movement and pupil features which allow us to reliably achieve this goal. We evaluate our proposed approach using several classifiers and examine how different subsets of features affect the performance. The results show about 82% accuracy on average for users wearing eye glasses and an average accuracy of 84.5% for users without eye glasses. Our results demonstrate that users' eye movement patterns and pupil behaviors can reveal valuable clues about their subjective mental workload and could be used in developing effective tools for unintentional insider threat detection and mitigation in real-world environments.

10aaccidental/unintentional incidents10aCompanies10aeye10aeye glasses10aeye movement patterns10aeye movements patterns10aFeature extraction10aGaze tracking10aGlass10ahuman error prediction10ainsider security incidents10apupil feature extraction10aSecurity10asecurity of data10asubjective mental workload10aTask analysis10aUIT detection10aunintentional insider threat detection10aVisualization1 aTakabi, Hassan1 aHashem, Yassir1 aDantu, Ram uhttps://nsl.cse.unt.edu/content/prediction-human-error-using-eye-movements-patterns-unintentional-insider-threat-detection00477nas a2200133 4500008004100000020001300041245006300054210005400117100002000171700002500191700002300216700001200239856009200251 2018 eng d a2391545500aOn the security of the Courtois-Finiasz-Sendrier signature0 asecurity of the CourtoisFiniaszSendrier signature1 aMorozov, Kirill1 aSarathi, Roy, Partha1 aRainer, Steinwandt1 aRui, Xu uhttps://www.degruyter.com/view/j/math.2018.16.issue-1/math-2018-0011/math-2018-0011.xml00917nas a2200145 4500008003900000245007100039210006900110520040200179100001600581700001900597700001800616700001500634700002600649856009600675 2018 d00aTechnologies Shaping Transportation of the Future and Smart Cities0 aTechnologies Shaping Transportation of the Future and Smart Citi3 a

Connected vehicles and smart cities are two massively transformational technologies. We are already seeing an impact with the investments in economy and society in the connected vehicles and cities. While the private-sector leads the connected car technology investments, the technological development and smart cities innovation is led by state and local governments. 
 

1 aDavis, Jeff1 aJohnson, Steve1 aLeVine, Minna1 aDantu, Ram1 aRojas-Levi, Elizabeth uhttps://nsl.cse.unt.edu/content/technologies-shaping-transportation-future-and-smart-cities00343nas a2200109 4500008004100000245003800041210003700079260001900116100001500135700001700150856006600167 2018 eng d00aTrue Matching of Employers' Needs0 aTrue Matching of Employers Needs aMiami, Florida1 aDantu, Ram1 aPaul, Aditya uhttps://nsl.cse.unt.edu/content/true-matching-employers-needs02864nas a2200505 4500008004100000245006200041210006200103260000800165520132800173653003301501653001801534653002901552653002601581653001901607653003001626653000901656653001701665653004801682653002201730653004101752653000901793653002701802653002101829653002401850653001301874653001601887653001101903653002301914653001901937653002701956653002901983653000802012653002302020653002302043653002202066653001402088653002002102653003602122653003702158653002302195100002302218700001502241700001902256856008302275 2018 eng d00aUninterrupted Video Surveillance in the Face of an Attack0 aUninterrupted Video Surveillance in the Face of an Attack cAug3 a

Distributed denial of service (DDoS) attacks continue to plague businesses and consumers alike, and due to an ever-growing digital landscape, these attacks are expected to grow in size and complexity. Current mitigation techniques ranging from hours to days are completely unacceptable given the cost and inconvenience these attacks place in our society. This paper puts forth three feedback control mechanisms to minimize the effects of DDoS attacks on real-time traffic. The first, called differentiated services code point (DSCP) Markdown, is a passive approach that uses micro firewall rules to lower the priority of out-of-profile packets while a second mechanism actively drops the out-of-profile packets based on rate and burst size parameters. The third technique uses parallel links when feedback is applied to stabilize the network after an attack has been detected. Results from all three techniques have shown to have a positive effect on real-time traffic. The first two approaches were able to stabilize network traffic in real-time, while the parallel links technique resulted in a slight delay. We validate the feedback mechanisms with our model that was generated using the system identification technique. Results show that the feedback architecture provides a fit accuracy with positive results.

10aattack mitigation techniques10aauthorisation10aautoregressive processes10aburst size parameters10aComputer crime10acomputer network security10aDDoS10aDDoS attacks10adifferentiated services code point markdown10aDiffServ networks10adistributed denial of service attack10aDSCP10aDSCP Markdown approach10afeedback control10afeedback mechanisms10aInternet10aIP networks10aJitter10aMathematical model10amicro-firewall10aout-of-profile packets10aparallel links technique10aQoS10aquality of service10areal-time services10areal-time systems10aResilient10aStreaming media10asystem identification technique10auninterrupted video surveillance10avideo surveillance1 aVempati, Jagannadh1 aDantu, Ram1 aThompson, Mark uhttps://nsl.cse.unt.edu/content/uninterrupted-video-surveillance-face-attack-001409nas a2200145 4500008004100000020002200041245005700063210005700120260002700177520095500204100002301159700001901182700001501201856004701216 2017 eng d a978-1-4503-4855-300aFeedback Control for Resiliency in Face of an Attack0 aFeedback Control for Resiliency in Face of an Attack aNew York, NY, USAbACM3 a

Distributed Denial of Service(DDoS) attacks are inevitable. The existing defensive mechanisms are relatively outdated. In this paper, we present a passive mechanism to reduce the impact of an attack on the network. We designed and implemented a robust feedback architecture, to maintain the stability of the network despite attacks. During an attack, the controller of the feedback architecture detects the irregularities in the response time and the necessary changes are made to the configuration to maintain the network in steady state. In this approach first, we model the network using black-box system identification technique. Second, we validate the model with test data by conducting various experiments such as varying the network topology. Last, we test the model with the feedback architecture built in our lab environment. Results show that the feedback architecture provides an average model fit accuracy with positive results.

1 aVempati, Jagannadh1 aThompson, Mark1 aDantu, Ram uhttp://doi.acm.org/10.1145/3064814.306481501730nas a2200133 4500008004100000245008700041210006900128260001200197520121200209100001901421700001901440700001501459856012201474 2017 eng d00aInsider Threat Detection Based on Users’ Mouse Movements and Keystrokes Behavior0 aInsider Threat Detection Based on Users Mouse Movements and Keys c10/20173 a

Insider threat is considered as one of the most  serious threats in cybersecurity and has been a prime security  concern for government and industry. Traditional approaches  can’t provide efficient solutions, and the threat keeps raising.  In this paper, we propose a new approach to insider threat  detection and prediction based on the user’s mouse movements  and keystrokes behavior. We conduct human subject experiments  with 30 participants and capture their mouse movements and  keystroke dynamics as they perform several computer-based  activities in both benign and malicious scenarios. We extract  features and evaluate our approach using several classifiers and  statistical analysis measures. The results show that participants  performing malicious tasks showed faster speed and longer mouse  movements, and long left click and keystroke duration than the  benign tasks. Our results suggest that users’ mouse movements  and keystrokes behavior can reveal valuable knowledge about  their malicious behavior and can be used as indicators in the  insider threat monitoring and detection frameworks.

1 aHashem, Yassir1 aTakabi, Hassan1 aDantu, Ram uhttps://nsl.cse.unt.edu/content/insider-threat-detection-based-users%E2%80%99-mouse-movements-and-keystrokes-behavior00630nas a2200193 4500008004100000020002200041245007300063210006900136260002700205653003100232653001700263653001900280653001700299100001900316700001900335700001500354700002000369856004700389 2017 eng d a978-1-4503-5177-500aA Multi-Modal Neuro-Physiological Study of Malicious Insider Threats0 aMultiModal NeuroPhysiological Study of Malicious Insider Threats aNew York, NY, USAbACM10aelectroencephalogram (eeg)10aeye tracking10ainsider threat10aneuroscience1 aHashem, Yassir1 aTakabi, Hassan1 aDantu, Ram1 aNielsen, Rodney uhttp://doi.acm.org/10.1145/3139923.313993004194nas a2200589 4500008004100000245008800041210006900129260000900198520239900207653002002606653002002626653005602646653001802702653001502720653001902735653001302754653001902767653001502786653001502801653001602816653001602832653002902848653002502877653001802902653001802920653002002938653002602958653001702984653003103001653003003032653003403062653002703096653002803123653003703151653001903188653002203207653004203229653000803271653002503279653001303304653001203317653001703329653001603346653001603362653000903378100002403387700001503411700002403426700001903450700002303469856011203492 2017 eng d00aOptimized and Secured Transmission and Retrieval of Vital Signs from Remote Devices0 aOptimized and Secured Transmission and Retrieval of Vital Signs  cJuly3 a

Smartphones and other mobile platforms provide a low cost and easily accessible method of monitoring patient health, and aid healthcare professionals in early detection of disease. Immediate access to the gathered data is an essential factor in effective patient care. But the current processes used for patients' vital data collection is slow and error prone. This undermines the advantages of remote monitoring that mobile platforms for health monitoring provide. In this paper, we propose to upload the patient health information to the Cloud. We investigate three different models to transfer data from the smartphone to the Cloud-perform all computations in the smartphone, perform all computations in the Cloud, and divide the computations between the smartphone and the Cloud. The second approach was found to be infeasible due to very high latency in data transfer with a delay of 2.84 seconds at an upload speed of 2500 KBytes per second. In order to protect the privacy of patients, it is required by law that the data gathered from remote monitoring by using mobile platforms must be kept private, and be secured before uploading to the Cloud. This paper explores the use of prominent public key encryption algorithms and their performance on a mobile device to securely transmit confidential electronic personal health information to the Cloud. We analyze performance of three common public key encryption schemes -RSA, Diffie-Hellman, and ECC. It is shown that 160 bit key size in ECC scheme provides the same level of security that a 1024 bit key size does in RSA and Diffie-Hellman. Further, the encryption and decryption time required by ECC is three times less than the other two schemes. Hence, ECC not only requires a smaller key size to provide the same level of security, but also faster encryption and decryption times as compared to the other two schemes. This makes ECC algorithms suitable to be implemented in resource constrained mobile platforms. We also compared ECC curves from three different standards - NIST, SECG, and Brainpool - to determine the optimum ECC curve, and key size to encrypt data in the mobile phone platform. It is shown that the Brainpool curve performed better than the other two standards when the key size is less than 521 bits. We also measured the latency of uploading encrypted data in a wide variety of WiFi and mobile networks.

10aBrainpool curve10aCloud computing10aconfidential electronic personal health information10adata transfer10adecryption10aDiffie-Hellman10aDiseases10aECC algorithms10aECC curves10aencryption10aerror prone10ahealth care10ahealthcare professionals10aMobile communication10amobile device10amobile health10amobile networks10amobile phone platform10apatient care10apatient health information10apatient health monitoring10apatient vital data collection10aPerformance evaluation10apublic key cryptography10apublic key encryption algorithms10aremote devices10aremote monitoring10aresource constrained mobile platforms10aRSA10asecured transmission10aSecurity10aservers10asmart phones10asmartphones10avital signs10aWiFi1 aThiyagaraja, Shanti1 aDantu, Ram1 aShrestha, Pradhumna1 aThompson, Mark1 aSmith, Christopher uhttps://nsl.cse.unt.edu/content/optimized-and-secured-transmission-and-retrieval-vital-signs-remote-devices00550nas a2200169 4500008004100000020001400041245009200055210006900147300001400216490000800230100001800238700001900256700002000275700001800295700001500313856005200328 2017 eng d a0002-914900aReal-Time Mobile Device-Assisted Chest Compression During Cardiopulmonary Resuscitation0 aRealTime Mobile DeviceAssisted Chest Compression During Cardiopu a196 - 2000 v1201 aSarma, Satyam1 aBucuti, Hakiza1 aChitnis, Anurag1 aKlacman, Alex1 aDantu, Ram uhttp://dx.doi.org/10.1016/j.amjcard.2017.04.00701278nas a2200205 4500008004100000022001600041245009200057210006900149260004300218520064900261653000900910653001200919653000900931653001100940653001000951100001500961700002700976700001801003856005101021 2016 eng d aUS9485345B200a911 services and vital sign measurement utilizing mobile phone sensors and applications0 a911 services and vital sign measurement utilizing mobile phone s aUSbUniversity of North Texasc11/20163 a

Improved methods for utilizing 911 services, for implementing 911 dispatch protocols, and for measuring vital signs of a human, all by accessing mobile phone sensors and applications, are disclosed. Vital signs such as heart rate, breathing rate, breathing distress, and blood pressure can be measured using mobile phone sensors and applications. A method for differential estimation of blood pressure involves the synchronization of time between two mobile phones, locating an appropriate position for one cell phone and recording heart sounds, and recording video data from the finger tip of the subject using the other mobile phone.

10adata10apatient10arate10aRemote10avideo1 aDantu, Ram1 aChandrasekaran, Vikram1 aGupta, Neeraj uhttps://patents.google.com/patent/US9485345/en02469nas a2200493 4500008004100000245005500041210005500096260000800151520099100159653001701150653001601167653002701183653002401210653001101234653001701245653001201262653002101274653001901295653002501314653003401339653002801373653002901401653003401430653002801464653003701492653002101529653003901550653002101589653003201610653002701642653001401669653001301683653002101696653001301717653001601730653003001746653002801776653001101804100002001815700001501835700002101850700002101871856008301892 2016 eng d00aAutomating ECU Identification for Vehicle Security0 aAutomating ECU Identification for Vehicle Security cDec3 a

The field of vehicular cybersecurity has received considerable media and research attention in the past few years. Given the increasingly connected aspect of consumer automobiles, along with the inherent danger of these machines, there has been a call for experienced security researchers to contribute towards the vehicle security domain. The proprietary nature of Controller Area Network (CAN) bus messages, however, creates a barrier of entry for those unfamiliar, due to the need to identify what the messages on a given vehicle's bus are broadcasting. This work aims to automate the process of correlating CAN bus messages with specific Electronic Control Unit (ECU) functions in a new vehicle, by creating a machine learning classifier that has been trained on a dataset of multiple vehicles from different manufacturers. The results show that accurate classification is possible, and that some ECUs that broadcast similar vehicle dynamics broadcast similar CAN messages.

10aAcceleration10aautomobiles10aautomotive electronics10aautomotive security10aBrakes10abroadcasting10aCAN bus10aCAN bus messages10aclassification10aconsumer automobiles10acontrol engineering computing10acontroller area network10acontroller area networks10aECU identification automation10aelectronic control unit10aelectronic engineering computing10aembedded systems10alearning (artificial intelligence)10amachine learning10amachine learning classifier10apattern classification10aProtocols10aSecurity10asecurity of data10aTraining10avehicle bus10avehicular ad hoc networks10avehicular cybersecurity10aWheels1 aJaynes, Michael1 aDantu, Ram1 aVarriale, Roland1 aEvans, Nathaniel uhttps://nsl.cse.unt.edu/content/automating-ecu-identification-vehicle-security00595nas a2200157 4500008004100000245010300041210006900144260000700213300001000220490000600230100001900236700001900255700002500274700001500299856012300314 2016 eng d00aInside the Mind of the Insider: Towards Insider Threat Detection Using Psychophysiological Signals0 aInside the Mind of the Insider Towards Insider Threat Detection  c02 a20-360 v61 aHashem, Yassir1 aTakabi, Hassan1 aGhasemiGol, Mohammad1 aDantu, Ram uhttps://nsl.cse.unt.edu/content/inside-mind-insider-towards-insider-threat-detection-using-psychophysiological-signals03075nas a2200217 4500008004100000022001400041245011100055210006900166300000600235520238000241653001902621653001502640653002302655653001702678653002602695653001902721653001302740100001802753700001502771856007102786 2016 eng d a0167-404800aNeurokey: towards a new paradigm of cancelable biometrics-based key generation using electroencephalograms0 aNeurokey towards a new paradigm of cancelable biometricsbased ke a-3 a

 Brain waves (Electroencephalograms, EEG) can provide conscious, continuous human authentication for the proposed system. The advantage of brainwave biometry is that it is nearly impossible to forge or duplicate as the neuronal activity of each person is unique even when they think about the same thing.

We propose exploiting the brain as a biometric physical unclonable function (PUF). A user's \{EEG\} signals can be used to generate a unique and repeatable key that is resistant to cryptanalysis and eavesdropping, even against an adversary who obtains all the information regarding the system. Another objective is to implement a simplistic approach of cancelable biometrics by altering one's thoughts.

Features for the first step, Subject Authentication, are obtained from each task using the energy bands obtained from Discrete Fourier Transform and Discrete Wavelet Transform. The second step constituting the Neurokey generation involves feature selection using normalized thresholds and segmentation window protocol.

We applied our methods to two datasets, the first based on five mental activities by seven subjects (325 samples) and the second based on three visually evoked tasks by 120 subjects (10,861 samples). These datasets were used to analyze the key generation process because they varied in the nature of data acquisition, environment, and activities. We determined the feasibility of our system using a smaller dataset first. We obtained a mean subject classification of 98.46% and 91.05% for Dataset I and Dataset İI\} respectively. After an appropriate choice of features, the mean half total error rate for generating Neurokeys was 3.05% for Dataset I and 4.53% for Dataset II, averaged over the subjects, tasks, and electrodes. A unique key was established for each subject and task, and the error rates were analyzed for the Neurokey generation protocol. \{NIST\} statistical suite of randomness tests were applied on all the sequences obtained from the Neurokey generation process.

A consistent, unique key for each subject can be obtained using \{EEG\} signals by collecting data from distinguishable cognitive activities. Moreover, the Neurokey can be changed easily by performing a different cognitive task, providing a means to change the biometrics in case of a compromise (cancelable).

10aAuthentication10abiometrics10acryptographic keys10acryptography10aelectroencephalograms10akey generation10aSecurity1 aBajwa, Garima1 aDantu, Ram uhttp://www.sciencedirect.com/science/article/pii/S016740481630066901637nas a2200337 4500008004100000245008600041210006900127260000900196520058000205653001200785653001900797653003400816653002600850653003100876653000800907653003200915653001900947653001900966653001600985653001001001653001501011653001001026653000901036653001601045653003901061653001901100653002601119100002101145700001501166856011801181 2016 eng d00aRealizing Optimal Chest Compression Fraction During Cardiopulmonary Resuscitation0 aRealizing Optimal Chest Compression Fraction During Cardiopulmon cJune3 a

Cardiopulmonary Resuscitation (CPR) is usually preformed in complex situations with multiple parties with a wide range of capabilities. These situations require intermediate pauses for defibrillation, applying advanced airways, and switching CPR administrators. One of the biggest unknowns if chest compression fraction (CCF), which is the optimal fraction of time spent applying compressions. Using the American Heart Association (AHA) guidelines for CPR and rational actor models from game theory, we show the validity of the recommended CCF set by the by the AHA.

10aairways10aCardiac arrest10acardiopulmonary resuscitation10acardiovascular system10aChest Compression Fraction10aCPR10aCPR administrator switching10adefibrillation10adefibrillators10agame theory10aGames10aGuidelines10aHeart10alung10aMeasurement10aoptimal chest compression fraction10apneumodynamics10arational actor models1 aTalkington, Josh1 aDantu, Ram uhttps://nsl.cse.unt.edu/content/realizing-optimal-chest-compression-fraction-during-cardiopulmonary-resuscitation01459nas a2200145 4500008004100000245008700041210006900128260001200197520092100209100001501130700001801145700001801163700002001181856011201201 2015 eng d00a Effective CPR Procedure With Real-Time Evaluation and Feedback Using Smartphones 0 aEffective CPR Procedure With RealTime Evaluation and Feedback Us c12/20153 a

A method for performing CPR, comprising activating an application on one or more mobile phones having one or more sensors, placing one or more mobile phones on the finger of a subject to collect information about the subject, determining whether CPR is necessary based on the collected information about the subject, calibrating the sensors of the one or more mobile phones, placing the one or more mobile phones in a position on a hand of a user of the one or more mobile phones, administering chest compressions to the subject, activating a sensor of the one or more mobile phones, including an accelerometer sensor, to permit the application to capture information about the chest compression rate and displacement relating to movement of the chest of the subject, and transmitting the chest compression rate and displacement information of the subject to the emergency dispatcher using the mobile phone.

1 aDantu, Ram1 aGupta, Neeraj1 aDantu, Vishnu1 aMorgan, Zachary uhttps://nsl.cse.unt.edu/content/effective-cpr-procedure-real-time-evaluation-and-feedback-using-smartphones00413nas a2200145 4500008004100000245005400041210005400095300000800149490000700157100001800164700001500182700001600197700001700213856003700230 2015 eng d00aFitts Law Extensions for Multiple Joint Movements0 aFitts Law Extensions for Multiple Joint Movements ae610 v961 aGupta, Neeraj1 aDantu, Ram1 aDantu, Siva1 aNana, Arvind uhttps://nsl.cse.unt.edu/node/17402111nas a2200469 4500008004100000245005300041210005100094260001200145520078900157653001500946653003400961653003900995653001801034653001401052653000801066653001601074653003001090653003101120653002801151653001601179653002801195653002101223653001201244653002501256653002101281653001801302653001401320653002201334653001601356653002501372653004401397653002601441653002101467653001201488653001701500653001501517100001801532700002101550700001801571700001501589856003701604 2015 eng d00aA framework for secured collaboration in mHealth0 aframework for secured collaboration in mHealth c06/20153 a

We have designed a novel framework of services, protocols and technologies to ensure the secure collaboration in M2M networks, specifically in mobile health. The promise of mobile health to reform preventive self-care opens new doors for remote monitoring to improve health care communication. With cardiopulmonary resuscitation (CPR) as an example, we classify our M2M elements into services, roles, human-computer protocols and technologies through which we require trust, anonymity, scalability, and active detachment. We simulate a scenario in which a patient needs CPR and through the use of widely available technologies (such as a smartphone and secure web sockets) we demonstrate a technological collaboration that facilitates secure emergency mobile health services.

10acardiology10acardiopulmonary resuscitation10aCardiopulmonary resuscitation(CPR)10aCollaboration10aComputers10aCPR10ahealth care10ahealth care communication10ahuman computer interaction10ahuman-computer protocol10aM2M network10amachine to machine(M2M)10aMedical services10amHealth10aMobile communication10amobile computing10amobile health10aProtocols10aremote monitoring10aScalability10asecure collaboration10asecure emergency mobile health services10asecured collaboration10asecurity of data10aservers10asmart phones10asmartphone1 aWidick, Logan1 aTalkington, Josh1 aBajwa, Garima1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/15701678nas a2200313 4500008004100000245006300041210006000104260000800164520078800172653003000960653002800990653001701018653001701035653002101052653001501073653001301088653003901101653002601140653002901166653002101195653002201216653001201238653001401250653001501264653001201279100002101291700001501312856003701327 2015 eng d00aAn opportunistic encryption extension for the DNS protocol0 aopportunistic encryption extension for the DNS protocol cMay3 a

Confidentiality for DNS transactions has been a low-priority concern in DNS security for a long time due to performance requirements for the functionality of DNS and the fact that data in the DNS is considered public. However, the information carried in DNS transactions, if collected and analyzed, can pose real threats to personal privacy. This makes DNS a good target for passive eavesdropping to collect data for many purposes some of which may be malicious. The protocol described in this document is intended to facilitate an opportunistic negotiation of encryption in the DNS to provide confidentiality for the last mile of DNS resolution. It defines procedures to discover encryption-aware servers and how to establish a relationship with them with minimum overhead.

10acomputer network security10acryptographic protocols10aDNS protocol10aDNS security10aDNS transactions10aencryption10aInternet10aopportunistic encryption extension10apassive eavesdropping10aperformance requirements10apersonal privacy10apose real threats10aPrivacy10aProtocols10aPublic key10aservers1 aBucuti, Theogene1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/15901677nas a2200349 4500008004100000245004300041210004100084260000800125520072100133653002600854653001900880653001600899653001400915653002700929653002600956653002500982653003101007653001301038653001401051653002801065653004001093653001601133653002501149653001301174653001701187653001901204653001501223100001801238700001501256700001901271856003701290 2015 eng d00aPass-pic: A mobile user authentication0 aPasspic A mobile user authentication cMay3 a

Conventional authentication methods utilizing alphanumeric username and passwords, PIN numbers, or any combination thereof have many weaknesses. On modern smart phones there are multiple ways users can authenticate. The traditional username password combination is used often as well as PIN passwords and pattern based passwords. The problem with these methods is that they are still vulnerable. A short password or to a much greater extent a PIN, or a pattern password can be defeated by various techniques such as smudge attacks, key loggers and so on. Our aim with Pass-Pic is to implement a picture based authentication system that is both more secure and easier for the user to both input and remember.

10aalphanumeric username10aAuthentication10akey loggers10aKeyboards10amessage authentication10amobile authentication10aMobile communication10amobile user authentication10apass-pic10apasswords10apattern based passwords10apicture based authentication system10aPIN numbers10aRandom access memory10aSecurity10asmart phones10asmudge attacks10aVibrations1 aBajwa, Garima1 aDantu, Ram1 aAldridge, Ryan uhttps://nsl.cse.unt.edu/node/16002248nas a2200385 4500008004100000245008700041210006900128260000800197520101400205653000801219653001401227653002901241653002701270653003001297653002201327653001701349653001901366653002001385653003101405653003201436653002301468653001101491653002901502653003001531653002201561653001301583653001201596653002601608653003501634653003001669100001801699700001701717700001501734856011301749 2015 eng d00aPhD Forum: A System Identification Approach to Monitoring Network Traffic Security0 aPhD Forum A System Identification Approach to Monitoring Network cNov3 a

Network security is a growing area of interest for cyber systems, especially given the increasing number of attacks on companies each year. Though there are a vast amount of tools already available, System Identification (SI) complements intrusion detection systems to help manage network traffic stability. SI is the science of building mathematical models of dynamic systems. This paper introduces the use of SI for modeling network traffic and utilizes a linear time invariant model to analyze performance of real connections and attack instances. We generated several ARX models where each represented a different threat state in the network. We utilized the KDD CUP 1999's DARPA dataset to analyze the performance when dealing with different attacks. Results show that the average model fit was 84.14% when determining if the system was experiencing normal traffic. This value is promising because it shows how well the system is able to determine a network state in a given time when fed input.

10aARX10aARX model10aautoregressive processes10aComputational modeling10acomputer network security10aComputer security10acyber system10adynamic system10aElectronic mail10aintrusion detection system10alinear time invariant model10aMathematical model10aModels10anetwork traffic security10anetwork traffic stability10aPredictive models10aSecurity10aSilicon10aSystem Identification10asystem identification approach10atelecommunication traffic1 aMayo, Quentin1 aBryce, Renee1 aDantu, Ram uhttps://nsl.cse.unt.edu/content/phd-forum-system-identification-approach-monitoring-network-traffic-security00420nas a2200133 4500008003900000245007600039210006900115300000800184490000700192100001800199700001500217700001700232856003700249 2015 d00aQuantifying Dynamic Cerebral Autoregulation using Electroencephalograms0 aQuantifying Dynamic Cerebral Autoregulation using Electroencepha ae690 v961 aBajwa, Garima1 aDantu, Ram1 aNana, Arvind uhttps://nsl.cse.unt.edu/node/17502139nas a2200445 4500008004100000245007500041210006900116260000800185520088000193653001901073653001201092653001501104653002201119653001601141653001701157653002501174653002501199653002101224653002301245653001701268653003101285653002701316653001401343653001201357653002101369653001301390653002501403653001201428653002201440653002401462653002201486653001601508653001701524653003101541653002901572100002301601700001701624700001501641856003701656 2015 eng d00aRandom anonymization of mobile sensor data: Modified Android framework0 aRandom anonymization of mobile sensor data Modified Android fram cMay3 a

With the increasing ability to accurately classify activities of mobile users from what was once viewed as innocuous mobile sensor data, the risk of users compromising their privacy has risen exponentially. Currently, mobile owners cannot control how various applications handle the privacy of their sensor data, or even determine if a service provider is adversarial or trustworthy. To address these privacy concerns, third party applications have been designed to allow mobile users to have control over the data that is sent to service providers. However, these applications require users to set flags and parameters that place restrictions on the anonymized or real sensor data that is sent to the requestor. Therefore, in this paper, we introduce a new framework, RANDSOM, that moves the decision-making from the application level to the operating system level.

10aAccelerometers10aAndroid10aanonymized10aapplication level10aData models10adata privacy10aHidden Markov models10aMobile communication10amobile computing10amobile sensor data10amobile users10amodified Android framework10aoperating system level10apervasive10aPrivacy10aprivacy concerns10aprovider10arandom anonymization10aRANDSOM10aRANDSOM framework10asensor data privacy10aservice providers10asmart phone10asmart phones10atelecommunication security10athird party applications1 aClaiborne, Cynthia1 aNcube, Cathy1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/15800662nas a2200193 4500008004100000020002200041245007100063210006900134260002700203653002900230653002600259653002900285653002900314100001900343700001900362700002500381700001500406856004700421 2015 eng d a978-1-4503-3824-000aTowards Insider Threat Detection Using Psychophysiological Signals0 aTowards Insider Threat Detection Using Psychophysiological Signa aNew York, NY, USAbACM10abrain computer interface10aelectroencephalograph10ainsider threat detection10aphysiological indicators1 aHashem, Yassir1 aTakabi, Hassan1 aGhasemiGol, Mohammad1 aDantu, Ram uhttp://doi.acm.org/10.1145/2808783.280879202938nas a2200553 4500008004100000245007200041210006900113260000800182520136300190653003101553653002501584653001701609653001301626653000901639653001801648653001601666653002201682653002801704653001501732653002001747653001201767653002201779653002201801653003201823653001201855653001901867653001601886653002401902653002201926653002701948653001301975653002901988653002102017653001302038653003202051653001802083653001902101653002702120653002502147653003602172653002302208653001802231653002602249100001802275700002002293700001502313700001902328856003702347 2015 eng d00aUnintentional bugs to vulnerability mapping in Android applications0 aUnintentional bugs to vulnerability mapping in Android applicati cMay3 a

The intention of an Android application, determined by the source code analysis is used to identify potential maliciousness in that application (app). Similarly, it is possible to analyze the unintentional behaviors of an app to identify and reduce the window of vulnerabilities. Unintentional behaviors of an app can be any developmental loopholes such as software bugs overlooked by a developer or introduced by an adversary intentionally. FindBugsTM and Android Lint are a couple of tools that can detect such bugs easily. A software bug can cause many security vulnerabilities (known or unknown) and vice-versa, thus, creating a many-to-many mapping. In our approach, we construct a matrix of mapping between the bugs and the potential vulnerabilities. A software bug detection tool is used to identify a list of bugs and create an empirical list of the vulnerabilities in an app. The many-to-many mapping matrix is obtained by two approaches - severity mapping and probability mapping. These mappings can be used as tools to measure the unknown vulnerabilities and their strength. We believe our study is the first of its kind and it can enhance the security of Android apps in their development phase itself. Also, the reverse mapping matrix (vulnerabilities to bugs) could be used to improve the accuracy of malware detection in Android apps.

10aAndroid (operating system)10aAndroid applications10aAndroid Lint10aAndroids10abugs10aComputer bugs10aConferences10adevelopment phase10adevelopmental loopholes10aFindBugsTM10aHumanoid robots10aIndexes10ainvasive software10amalware detection10amany-to-many mapping matrix10amapping10amatrix algebra10aprobability10aprobability mapping10aprogram debugging10areverse mapping matrix10aSecurity10asecurity vulnerabilities10aseverity mapping10aSoftware10asoftware bug detection tool10asoftware bugs10asoftware tools10asource code (software)10asource code analysis10aunintentional behavior analysis10aunintentional bugs10avulnerability10avulnerability mapping1 aBajwa, Garima1 aFazeen, Mohamed1 aDantu, Ram1 aTanpure, Sonal uhttps://nsl.cse.unt.edu/node/25203351nas a2200433 4500008004100000245005700041210005500098260000900153520210500162653004602267653002502313653001302338653001602351653001302367653002302380653002002403653001202423653002002435653002202455653003902477653002702516653002202543653001202565653002302577653002102600653002402621653000802645653003102653653001002684653002902694653001702723653002702740653002702767653002502794653002602819100002002845700001502865856003702880 2014 eng d00aAnother free app: Does it have the right intentions?0 aAnother free app Does it have the right intentions cJuly3 a

Security and privacy holds a great importance in mobile devices due to the escalated use of smart phone applications (app). This has made the user even more vulnerable to malicious attacks than ever before. We aim to address this problem by proposing a novel framework to identify potential Android malware apps by extracting the intention and their permission requests. First, we constructed a dataset consisting of 1,730 benign apps along with 273 malware samples. Then, both datasets were subjected to source code extraction. From there on, we followed a two phase approach to identify potential malware samples. In phase 1, we constructed a machine learning model to group benign apps into different clusters based on their operations known as the task-intention. Once we trained the model, it was used to identify the task-intention of an Android app. Further, in this phase, we only used the benign apps to construct the task-intentions and none of the malware signatures were involved. Therefore, our approach does not use machine learning models to identify malware apps. Then, for each task-intention group, we extracted the permission-requests of the apps and constructed the probability mass functions (PMF). We named the shape of this PMF as Intention-Shape or I-Shape. In phase 2, we used the permission-requests, task-intentions and I-Shapes to identify potential malware apps. We compared the permission-requests of an unknown app with its corresponding I-Shape to identify the potential malware apps. Using this approach, we obtained an accuracy of 89% in detecting potential malware samples. The novelty of our work is to perform potential malware identification without training any models with malware signatures, and utilization of I-Shapes to identify such potential malware samples. Our approach can be utilized to identify the safety of an app before it is installed as it performs static code analysis. Further, it can be utilized in pre-screening or multi-layer security sys- ems. It is also highly useful in screening malware apps when launching in Android markets.

10aAndroid app task-intention identification10aAndroid malware apps10aAndroids10abenign apps10aclusters10aFeature extraction10aHumanoid robots10aI-Shape10aintention-shape10ainvasive software10alearning (artificial intelligence)10amachine learning model10amalicious attacks10aMalware10aMathematical model10amobile computing10apermission-requests10aPMF10aprobability mass functions10aShape10asmart phone applications10asmart phones10asource code (software)10asource code extraction10astatic code analysis10aUnsupervised learning1 aFazeen, Mohamed1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/23401983nas a2200205 4500008004100000020002200041245006000063210005900123260002700182520139100209653001201600653001801612653001501630653002301645653000901668100002001677700001801697700001501715856004701730 2014 eng d a978-1-4503-2812-800aContext-aware Multimedia Encryption in Mobile Platforms0 aContextaware Multimedia Encryption in Mobile Platforms aNew York, NY, USAbACM3 a

Voice over IP (VoIP) is a part of multimedia content and this communication is growing rapidly in portable devices due to its attractive features. Secure communication is critical as most of such communications are routed through public channels. Establishing secure VoIP communication is computationally expensive. Modern high strength encryption algorithms such as AES, RSA, Serpent, etc. need high computational power for encryption. On the mobile platform this is a significant factor due to its constrained power resources. In this work we are presenting a novel idea of encrypting VoIP speech data while conserving resources without compromising the security of the VoIP communication. First, the algorithm detects the content of the speech data and identifies its context. Then sensitive sections of the conversation are separated. In the last step, these sections are encrypted with a high strength cryptographic algorithm while other parts are encrypted with a less strength algorithm for better performance. In this way unnecessary encryption power is spared. This will conserve computational power while ensuring the security of sensitive information. Also, we discuss some of the crucial potential attack vectors and their defense mechanisms. Finally, we implemented a prototype to test our concept and we observed an average of 39% reduction in computational time.

10aAndroid10acontext-aware10aencryption10aspeech recognition10aVoIP1 aFazeen, Mohamed1 aBajwa, Garima1 aDantu, Ram uhttp://doi.acm.org/10.1145/2602087.260211502255nas a2200457 4500008004100000022001400041245008500055210006900140300000900209490000600218520096800224653001701192653001901209653001001228653002801238653003501266653001501301653002201316653002601338653000801364653001901372653001801391653002501409653001301434653002601447653002901473653002201502653002901524653001101553653002201564653001901586653002501605653002201630653001701652653001601669653002401685100001801709700001801727700001501745856003701760 2014 eng d a2168-237200aEffective CPR Procedure With Real Time Evaluation and Feedback Using Smartphones0 aEffective CPR Procedure With Real Time Evaluation and Feedback U a1-110 v23 a

Timely cardio pulmonary resuscitation (CPR) can mean the difference between life and death. A trained person may not be available at emergency sites to give CPR. Normally, a 9-1-1 operator gives verbal instructions over the phone to a person giving CPR. In this paper, we discuss the use of smartphones to assist in administering CPR more efficiently and accurately. The two important CPR parameters are the frequency and depth of compressions. In this paper, we used smartphones to calculate these factors and to give real-time guidance to improve CPR. In addition, we used an application to measure oxygen saturation in blood. If blood oxygen saturation falls below an acceptable threshold, the person giving CPR can be asked to do mouth-to-mouth breathing. The 9-1-1 operator receives this information real time and can further guide the person giving CPR. Our experiments show accuracy >90% for compression frequency, depth, and oxygen saturation.

10aAcceleration10aAccelerometers10ablood10ablood oxygen saturation10acardio pulmonary resuscitation10acardiology10acompression depth10acompression frequency10aCPR10aCPR parameters10aCPR procedure10adepth of compression10aFeedback10aFrequency measurement10afrequency of compression10amedical computing10amouth-to-mouth breathing10aOxygen10aoxygen saturation10apneumodynamics10areal-time evaluation10areal-time systems10asmart phones10asmartphones10averbal instructions1 aGupta, Neeraj1 aDantu, Vishnu1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/14602289nas a2200457 4500008004100000245005500041210005500096260000800151520093700159653003101096653002101127653002501148653002601173653002201199653001501221653003301236653003401269653003101303653003201334653002701366653002801393653002101421653001001442653002301452653002401475653003001499653001501529653002201544653002301566653002301589653002901612653002701641653001701668653001601685100002401701700002301725700001501748700001501763700001601778856003701794 2014 eng d00aSmart phone monitoring of second heart sound split0 aSmart phone monitoring of second heart sound split cAug3 a

Heart Auscultation (listening to heart sounds) is the basic element of cardiac diagnosis. The interpretation of these sounds is a difficult skill to acquire. In this work we have developed an application to detect, monitor, and analyze the split in second heart sound (S2) using a smart phone. The application records the heartbeat using a stethoscope connected to the smart phone. The audio signal is converted into the frequency domain using Fast Fourier Transform to detect the first and second heart sounds (S1 and S2). S2 is extracted and fed into the Discrete Wavelet Transform (DWT) and then to Continuous Wavelet Transform (CWT) to detect the Aortic (A2) and the Pulmonic (P2) components, which are used to calculate the split in S2. With our application, users can continuously monitor their second heart sound irrespective of ages and check for a split in their hearts with a low-cost, easily available equipment.

10aacoustic signal processing10aaortic component10abiomedical equipment10aBiomedical monitoring10acardiac diagnosis10acardiology10acontinuous wavelet transform10aContinuous wavelet transforms10adiscrete wavelet transform10adiscrete wavelet transforms10afast Fourier transform10afast Fourier transforms10afrequency domain10aHeart10aheart auscultation10aheartbeat recording10amedical signal processing10aMonitoring10apatient diagnosis10apatient monitoring10apulmonic component10asecond heart sound split10asmart phone monitoring10asmart phones10astethoscope1 aThiyagaraja, Shanti1 aVempati, Jagannadh1 aDantu, Ram1 aSarma, Tom1 aDantu, Siva uhttps://nsl.cse.unt.edu/node/15601775nas a2200421 4500008004100000245005600041210005500097260001200152520060600164653001700770653001400787653003500801653001200836653002900848653003800877653003100915653001500946653001300961653003000974653002101004653001601025653001801041653001001059653001101069653002301080653001701103653003401120653001301154653001001167653002801177653001301205653003101218653002101249653001101270100002001281700001501301856003701316 2014 eng d00aTire-road friction estimation utilizing smartphones0 aTireroad friction estimation utilizing smartphones c08/20143 a

Tire-road friction is an important parameter for a number of different safety features present in modern-day vehicles, and the knowledge of this friction may also prove useful to the driver of a vehicle while it is in motion. In particular, this information may help inform a driver of dangerous low-traction situations that he or she may need to be aware of. Furthermore, since a growing number of drivers have access to Bluetooth-enabled smartphones, it is worth exploring how these devices may be leveraged in concert with vehicular CAN-bus networks to provide valuable safety information.

10aAcceleration10aBluetooth10abluetooth-enabled smart phones10aCAN-bus10acontroller area networks10adangerous low-traction situations10adriver information systems10aEstimation10afriction10agraphical user interfaces10amobile computing10aroad safety10aroad vehicles10aRoads10aSafety10asafety information10asmart phones10atire-road friction estimation10atraction10atyres10avehicle safety features10aVehicles10avehicular CAN-bus networks10avehicular safety10aWheels1 aJaynes, Michael1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/15500347nas a2200121 4500008004100000245003800041210003800079260001300117100002300130700002000153700001500173856003700188 2013 eng d00aAndroid Sensor Data Anonymization0 aAndroid Sensor Data Anonymization bSpringer1 aClaiborne, Cynthia1 aFazeen, Mohamed1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/17201184nas a2200181 4500008004100000020002200041245006700063210006700130260013200197520048700329653001900816653002800835653002400863653002600887100001800913700001500931856005600946 2013 eng d a978-1-936968-89-300aCerebral Autoregulation Assessment Using Electroencephalograms0 aCerebral Autoregulation Assessment Using Electroencephalograms aICST, Brussels, Belgium, BelgiumbICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering)3 a

This paper presents the possibility of using Electroencephalograms (EEG) signals of an individual for quantitative interpretation of Cerebral Autoregulation (CA). EEG data was recorded during arm cuff inflation to induce dynamic changes in arterial blood pressure and then, Cerebral Blood Flow (CBF) was estimated from EEG using canonical hemodynamic response function (HRF). The assessment of CA was carried out by using power of the various frequency bands of EEG signal.

10aBlood pressure10acerebral autoregulation10acerebral blood flow10aelectroencephalograms1 aBajwa, Garima1 aDantu, Ram uhttp://dx.doi.org/10.4108/icst.bodynets.2013.25370302206nas a2200313 4500008004100000245007100041210006900112300001600181490000700197520133800204653001901542653001301561653001501574653001701589653001001606653001601616653001801632653002501650653001701675653002001692653001101712653002601723100002701749700001501776700002201791700002401813700001801837856003701855 2013 eng d00aCuffless Differential Blood Pressure Estimation Using Smart Phones0 aCuffless Differential Blood Pressure Estimation Using Smart Phon a1080 - 10890 v603 a

Smart phones today have become increasingly popular with the general public for their diverse functionalities such as navigation, social networking, and multimedia facilities. These phones are equipped with high-end processors, high-resolution cameras, and built-in sensors such as accelerometer, orientation-sensor, and light-sensor. According to comScore survey, 26.2% of U.S. adults use smart phones in their daily lives. Motivated by this statistic and the diverse capability of smart phones, we focus on utilizing them for biomedical applications. We present a new application of the smart phone with its built-in camera and microphone replacing the traditional stethoscope and cuff-based measurement technique, to quantify vital signs such as heart rate and blood pressure. We propose two differential blood pressure estimating techniques using the heartbeat and pulse data. The first method uses two smart phones whereas the second method replaces one of the phones with a customized external microphone. We estimate the systolic and diastolic pressure in the two techniques by computing the pulse pressure and the stroke volume from the data recorded. By comparing the estimated blood pressure values with those measured using a commercial blood pressure meter, we obtained encouraging results of 95–100% accuracy.

10aBlood pressure10acuffless10aEstimation10afinger pulse10aHeart10aMicrophones10amobile camera10aMobile communication10amobile phone10aSynchronization10aValves10avascular transit time1 aChandrasekaran, Vikram1 aDantu, Ram1 aJonnada, Srikanth1 aThiyagaraja, Shanti1 aSubbu, Kalyan uhttps://nsl.cse.unt.edu/node/14701188nas a2200169 4500008004100000020002200041245005600063210005600119260002700175520068100202653001400883653002400897653001700921100001800938700001500956856004700971 2013 eng d a978-1-4503-1973-700aEvaluation of Respiration Quality Using Smart Phone0 aEvaluation of Respiration Quality Using Smart Phone aNew York, NY, USAbACM3 a

Breathing is one of the vital signs that are considered important from medical point of view. The quality of breathing is evaluated by considering several factors. In this paper we present the results of experiments that use a smart phone to evaluate some of the factors to determine the quality of breathing. The accelerometer in the smart phone is used to measure the breathing. We measure subjects with normal breathing, slow breathing, fast breathing and irregular breathing. Our results show that we can evaluate the rate of breathing using a smart phone with an accuracy ranging from 95% to 100%. We can also evaluate the regularity and the effort of breathing.

10a911 calls10arespiration quality10asmart phones1 aGupta, Neeraj1 aDantu, Ram uhttp://doi.acm.org/10.1145/2504335.250436401426nas a2200181 4500008004100000020002200041245005200063210005200115260013200167520077700299653002201076653001701098653001801115653001601133100002401149700001501173856005601188 2013 eng d a978-1-936968-89-300aFinger Blood Flow Monitoring Using Smart Phones0 aFinger Blood Flow Monitoring Using Smart Phones aICST, Brussels, Belgium, BelgiumbICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering)3 a

The use of smart phones in healthcare applications is growing steadily. The inbuilt sensors are used to estimate the value of physiological data from human body. With progressive innovation, smart phone based medical applications will continue to be developed at an exponential rate. In this paper, we show that a smart phone can be used to monitor the blood flow in finger, based on the pulse height obtained from the fingertips. This is achieved by using the camera lens and the flash light of the smart phone. The height of the pulse rises along with the surrounding temperature indicating that the blood flow increases when the temperature becomes warmer. This study shows that there is a potential to monitor regulation of body temperature using smart phone.

10afinger blood flow10afinger pulse10amobile health10asmart phone1 aThiyagaraja, Shanti1 aDantu, Ram uhttp://dx.doi.org/10.4108/icst.bodynets.2013.25370402179nas a2200205 4500008004100000022001400041245007400055210006900129300001700198490000600215520157700221653002401798653002001822653001601842653001501858100001801873700002001891700001501911856004701926 2013 eng d a2157-690400aLocateMe: Magnetic-fields-based Indoor Localization Using Smartphones0 aLocateMe Magneticfieldsbased Indoor Localization Using Smartphon a73:1–73:270 v43 a

Fine-grained localization is extremely important to accurately locate a user indoors. Although innovative solutions have already been proposed, there is no solution that is universally accepted, easily implemented, user centric, and, most importantly, works in the absence of GSM coverage or WiFi availability. The advent of sensor rich smartphones has paved a way to develop a solution that can cater to these requirements.

By employing a smartphone's built-in magnetic field sensor, magnetic signatures were collected inside buildings. These signatures displayed a uniqueness in their patterns due to the presence of different kinds of pillars, doors, elevators, etc., that consist of ferromagnetic materials like steel or iron. We theoretically analyze the cause of this uniqueness and then present an indoor localization solution by classifying signatures based on their patterns. However, to account for user walking speed variations so as to provide an application usable to a variety of users, we follow a dynamic time-warping-based approach that is known to work on similar signals irrespective of their variations in the time axis.

Our approach resulted in localization distances of approximately 2m--6m with accuracies between 80--100% implying that it is sufficient to walk short distances across hallways to be located by the smartphone. The implementation of the application on different smartphones yielded response times of less than five secs, thereby validating the feasibility of our approach and making it a viable solution.

10aIndoor localization10aMagnetic fields10asmartphones10aubiquitous1 aSubbu, Kalyan1 aGozick, Brandon1 aDantu, Ram uhttp://doi.acm.org/10.1145/2508037.250805400358nas a2200121 4500008004100000245004500041210004400086260001300130100002300143700001800166700001500184856003700199 2013 eng d00aNFC Based Two-Pass Mobile Authentication0 aNFC Based TwoPass Mobile Authentication bSpringer1 aVempati, Jagannadh1 aBajwa, Garima1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/17901608nas a2200181 4500008004100000020002200041245007000063210006900133260002700202520103400229653002401263653002501287653001401312653002001326100001801346700001501364856004701379 2013 eng d a978-1-4503-1973-700aQuantifying Cognitive Impairment Due to Physical or Mental Stress0 aQuantifying Cognitive Impairment Due to Physical or Mental Stres aNew York, NY, USAbACM3 a

In this paper, we study impairment caused by physical stress and impairment caused by alcohol consumption. We first base line the EEG waves in a meditation state. Then we measure the EEG waves during the physical activities such as walking, climbing stairs and doing sit-ups. We also measure the effect on brain as a person spins while sitting in a revolving chair (simulating a mental stress). Finally, we measure the EEG waves after consumption of alcohol. Our study shows that EEG waves do capture the physical activities that cause impairment. The magnitude of EEG waves increases with increased intensity of stress as measured by physical exercise or alcohol consumption. The magnitude is highest for sit-ups as compared to other activities and the magnitude for sit-ups after alcohol is even higher when compared with magnitude before alcohol consumption. A higher magnitude means lower level of alertness. The results could be used to improve the care of elderly and plan the intensity of their physical activity.

10aalcohol consumption10acognitive impairment10aEEG waves10aphysical stress1 aGupta, Neeraj1 aDantu, Ram uhttp://doi.acm.org/10.1145/2504335.250438401256nas a2200181 4500008004100000245005100041210004800092520069500140653003000835653003300865653002700898653001600925100001800941700001500959700002000974700001600994856006401010 2013 eng d00aSelf-Tracking via Brain-Mobile-Cloud Interface0 aSelfTracking via BrainMobileCloud Interface3 a

Abnormalities in the brain are one of the leading causes of disability amongst people. There is a significant delay between monitoring the onset of these disorders and their treatments. This paper presents a brain-mobile-cloud interface (BMCI) to integrate the mobile platform, cloud computing technology and existing brain monitoring systems to remotely monitor the brain signals of an individual using their electroencephalograms (EEGs) in unconventional environments. Further, we discuss the potential of our proposed framework in applications like tracking mental activities, identifying distracted driving behavior and their corresponding changes in cerebral blood flow (CBF).

10aCerebral Blood Flow (CBF)10aElectroencephalography (EEG)10aMobile cloud Interface10asmart phone1 aBajwa, Garima1 aDantu, Ram1 aFazeen, Mohamed1 aJoseph, Raj uhttp://www.aaai.org/ocs/index.php/SSS/SSS13/paper/view/580301976nas a2200253 4500008004100000022001400041245007300055210006900128300001400197490000700211520128800218653002301506653001801529653001201547653000901559653001101568653000801579653001801587653000901605100002701614700001501641700001801656856004801674 2013 eng d a1380-750100aSocio-technical Aspects of Remote Media Control for a NG9-1-1 System0 aSociotechnical Aspects of Remote Media Control for a NG911 Syste a733–7590 v623 a

9-1-1 emergency calls mostly involve distress situations that cause people to panic while trying to answer questions or follow instructions given by a dispatcher. To obtain precious information with the least user intervention and reduced stress on the user, there is a need for the dispatcher to have a better control and understanding of the condition or situation at the other end. The increasing growth of smartphones embedded with camera, speaker phone, GPS, microphone and various other sensors, extends their usage from merely making calls to life saving gadgets during critical situations. By integrating these sensor rich smartphones and the rapidly growing VoIP technology, we propose a VoIP based Next Generation 9-1-1 (NG9-1-1) system for remote media control. Specifically, we use Session Initiation Protocol (SIP) in the implementation of the system using a mobile and a PC client. The proposed system on the mobile client accounted for less than 25% of CPU utilization even with video transmission. The average network utilization was about 10 and 72 kbps for audio and video, respectively. With these encouraging results, we believe the proposed remote media control system will facilitate information acquisition and decision making in emergency situations.

10aImage transmission10aMedia control10aNG9-1-110aPSAP10aRemote10aSIP10aVoice quality10aVoIP1 aChandrasekaran, Vikram1 aDantu, Ram1 aSubbu, Kalyan uhttp://dx.doi.org/10.1007/s11042-011-0875-100477nas a2200157 4500008004100000020002200041245004900063210004900112260002800161300001400189100001700203700001500220700001800235700001500253856005100268 2012 eng d a978-1-4471-2969-100aEvent Detection Based on Call Detail Records0 aEvent Detection Based on Call Detail Records aLondonbSpringer London a305–3161 aZhang, Huiqi1 aDantu, Ram1 aCao, Longbing1 aYu, Philip uhttp://dx.doi.org/10.1007/978-1-4471-2969-1_1901532nas a2200205 4500008004100000245003700041210003700078520097800115653001801093653001701111653002001128653001201148653001901160100002001179700002001199700001501219700001901234700002501253856004801278 2012 eng d00aSafe Driving Using Mobile Phones0 aSafe Driving Using Mobile Phones3 a

As vehicle manufacturers continue to increase their emphasis on safety with advanced driver-assistance systems (ADASs), we propose a device that is not only already in abundance but portable enough as well to be one of the most effective multipurpose devices that are able to analyze and advise on safety conditions. Mobile smartphones today are equipped with numerous sensors that can help to aid in safety enhancements for drivers on the road. In this paper, we use the three-axis accelerometer of an Android-based smartphone to record and analyze various driver behaviors and external road conditions that could potentially be hazardous to the health of the driver, the neighboring public, and the automobile. Effective use of these data can educate a potentially dangerous driver on how to safely and efficiently operate a vehicle. With real-time analysis and auditory alerts of these factors, we can increase a driver’s overall awareness to maximize safety.

10aAccelerometer10amobile phone10aroad conditions10asensors10avehicle safety1 aFazeen, Mohamed1 aGozick, Brandon1 aDantu, Ram1 aBhukhiya, Moiz1 aGonzález, Marta, C. uhttp://dx.doi.org/10.1109/TITS.2012.218764001396nas a2200217 4500008004100000020002200041245005500063210005500118300001400173520074000187653000800927653001300935653003200948653002500980653002301005653001801028100001801046700001501064700002401079856007501103 2012 eng d a978-0-12-415815-300aSecurity Issues in VoIP Telecommunication Networks0 aSecurity Issues in VoIP Telecommunication Networks a763–7893 aAs VoIP telecommunication networks are becoming popular, more and more VoIP calls are being made to accomplish security critical activities, e.g., E911 services, phone banking. However, the security ramifications of using VoIP have not been fully recognized, and there exists a substantial gap in the understanding of the potential impact of VoIP exploits on the VoIP users. In this chapter, we describe the components and functionalities of non-P2P and P2P VoIP networks and discuss the potential attacks to them such as MITM, spoofing, wiretapping, pharming, etc. We also illustrate a mechanism of using small world network to improve call performance of a P2P VoIP system and evaluate it over the currently deployed OpenVoIP system.10aP2P10aSecurity10asession initiation protocol10asmall world networks10atelecommunications10avoice over IP1 aYang, Xiaohui1 aDantu, Ram1 aWijesekera, Duminda uhttps://www.sciencedirect.com/science/article/pii/B978012415815300030301158nas a2200169 4500008004100000020002200041245004200063210004100105260002800146300001400174520068400188100001700872700001500889700001800904700001500922856005100937 2012 eng d a978-1-4471-2969-100aSmart Phone: Predicting the Next Call0 aSmart Phone Predicting the Next Call aLondonbSpringer London a317–3253 a

Prediction of incoming calls can be useful in many applications such as social networks, (personal, business) calendar and avoiding voice spam. Predicting incoming calls using just the context is a challenging task. We believe that this is a new area of research in context-aware ambient intelligence. In this paper, we propose a call prediction scheme and investigate prediction based on callers’ behavior and history. We present Holt-Winters method to predict calls from frequent and periodic callers. The Holt-Winters method shows high accuracy. Prediction and efficient scheduling of calls can improve the security, productivity and ultimately the quality of life.

1 aZhang, Huiqi1 aDantu, Ram1 aCao, Longbing1 aYu, Philip uhttp://dx.doi.org/10.1007/978-1-4471-2969-1_2003604nas a2200241 4500008004100000022001400041245004300055210004200098300001700140490000600157520297600163653001303139653001403152653001603166653002103182653001503203653001903218100002803237700001503265700001703280700001803297856004703315 2011 eng d a1556-466500aBehavior-based Adaptive Call Predictor0 aBehaviorbased Adaptive Call Predictor a21:1–21:280 v63 a

Predicting future calls can be the next advanced feature of the next-generation telecommunication networks as the service providers are looking to offer new services to their customers. Call prediction can be useful to many applications such as planning daily schedules, avoiding unwanted communications (e.g. voice spam), and resource planning in call centers. Predicting calls is a very challenging task. We believe that this is an emerging area of research in ambient intelligence where the electronic devices are sensitive and responsive to people’s needs and behavior. In particular, we believe that the results of this research will lead to higher productivity and quality of life. In this article, we present a Call Predictor (CP) that offers two new advanced features for the next-generation phones namely “Incoming Call Forecast” and “Intelligent Address Book.” For the Incoming Call Forecast, the CP makes the next-24-hour incoming call prediction based on recent caller’s behavior and reciprocity. For the Intelligent Address Book, the CP generates a list of most likely contacts/numbers to be dialed at any given time based on the user’s behavior and reciprocity. The CP consists of two major components: Probability Estimator (PE) and Trend Detector (TD). The PE computes the probability of receiving/initiating a call based on the caller/user’s calling behavior and reciprocity. We show that the recent trend of the caller/user’s calling pattern has higher correlation to the future pattern than the pattern derived from the entire historical data. The TD detects the recent trend of the caller/user’s calling pattern and computes the adequacy of historical data in terms of reversed time (time that runs towards the past) based on a trace distance. The recent behavior detection mechanism allows CP to adapt its computation in response to the new calling behaviors. Therefore, CP is adaptive to the recent behavior. For our analysis, we use the real-life call logs of 94 mobile phone users over nine months, which were collected by the Reality Mining Project group at MIT. The performance of the CP is validated for two months based on seven months of training data. The experimental results show that the CP performs reasonably well as an incoming call predictor (Incoming Call Forecast) with false positive rate of 8%, false negative rate of 1%, and error rate of 9%, and as an outgoing call predictor (Intelligent Address Book) with the accuracy of 70% when the list has five entries. The functionality of the CP can be useful in assisting its user in carrying out everyday life activities such as scheduling daily plans by using the Incoming Call Forecast, and saving time from searching for the phone number in a typically lengthy contact book by using the Intelligent Address Book. Furthermore, we describe other useful applications of CP besides its own aforementioned features including Call Firewall and Call Reminder.

10abehavior10acall logs10acall matrix10aconvergence time10aPrediction10atrace distance1 aPhithakkitnukoon, Santi1 aDantu, Ram1 aClaxton, Rob1 aEagle, Nathan uhttp://doi.acm.org/10.1145/2019583.201958801047nas a2200217 4500008004100000245004600041210004600087520046500133653001400598653002000612653001300632653001000645653002700655653001200682653001700694653002600711653001200737100002800749700001500777856003700792 2011 eng d00aCurrent and Future Trends in Social Media0 aCurrent and Future Trends in Social Media3 a

Social networking has been the biggest cultural shift since the industrial revolution, attracting millions of people, creating an ever-expanding social web, and revolutionizing the way we communicate. Although many changes have occurred since the fledgling steps of social networking and what it has evolved into today, improvement is a never-ending cycle. Thus, in this paper, additional methods will be explored to advance social networking overall.

10aBuildings10aElectronic mail10aFacebook10aMedia10aOnline Social Networks10aPrivacy10aSocial Media10aSocial Network Trends10aTwitter1 aBaatarjav, Enkh-Amgalan1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/25002229nas a2200277 4500008004100000020002200041245005100063210005000114260001800164520146300182653001701645653001801662653001901680653002101699653001401720653001501734653002101749653002501770653002001795653001701815653002301832100002601855700001801881700001501899856003701914 2011 eng d a978-1-4577-0652-300aEvaluation of gyroscope-embedded mobile phones0 aEvaluation of gyroscopeembedded mobile phones aAnchorage, AK3 a

Many mobile phone applications such as pedometers and navigation systems rely on orientation sensors that most smartphones are now equipped with. Unfortunately, these sensors rely on measured accelerometer and magnetic field data to determine the orientation. Thus, accelerations upon the phone which arise from everyday use alter orientation information. Similarly, external magnetic interferences from indoor/urban settings affect the heading calculation, resulting in inaccurate directional information. The inability to determine the orientation during everyday use inhibits many potential mobile applications development. In this work, we exploit the newly built-in gyroscope in the Nexus S smartphone to address the interference problems associated with the orientation sensor. We first perform drift error analysis and apply this to gyroscope calculations. We test simple as well as complex rotations seen in walking applications. We lastly test the gyroscope's resistance to described interferences. Experiments show angular calculations with percent error no larger than 6% from actual rotated values. Further, we are able to determine the phone's orientation at any time, in magnetically-interfered areas, with the phone accelerating. With this accurate information we can virtually orient the phone to better use mobile-acquired data. This shows that the presence of a gyroscope in smartphones will certainly aid in numerous applications.

10aAcceleration10aAccelerometer10aAccelerometers10aAngular rotation10aGyroscope10aGyroscopes10aMagnetic sensors10aMobile communication10aMobile handsets10amobile phone10aOrientation sensor1 aBarthold, Christopher1 aSubbu, Kalyan1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/24202573nas a2200241 4500008004100000022001400041245013800055210006900193300001400262490000600276520177600282653006002058653001602118653000802134653003002142653001802172653002002190653001202210100002002222700001502242700002602257856004802283 2011 eng d a1869-546900aIdentification of leaders, lurkers, associates and spammers in a social network: context-dependent and context-independent approaches0 aIdentification of leaders lurkers associates and spammers in a s a241–2540 v13 a

In this paper, we present two methods for classification of different social network actors (individuals or organizations) such as leaders (e.g., news groups), lurkers, spammers and close associates. The first method is a two-stage process with a fuzzy-set theoretic (FST) approach to evaluation of the strengths of network links (or equivalently, actor-actor relationships) followed by a simple linear classifier to separate the actor classes. Since this method uses a lot of contextual information including actor profiles, actor-actor tweet and reply frequencies, it may be termed as a context-dependent approach. To handle the situation of limited availability of actor data for learning network link strengths, we also present a second method that performs actor classification by matching their short-term (say, roughly 25 days) tweet patterns with the generic tweet patterns of the prototype actors of different classes. Since little contextual information is used here, this can be called a context-independent approach. Our experimentation with over 500 randomly sampled records from a twitter database consists of 441,234 actors, 2,045,804 links, 6,481,900 tweets, and 2,312,927 total reply messages indicates that, in the context-independent analysis, a multilayer perceptron outperforms on both on classification accuracy and a new F-measure for classification performance, the Bayes classifier and Random Forest classifiers. However, as expected, the context-dependent analysis using link strengths evaluated using the FST approach in conjunction with some actor information reveals strong clustering of actor data based on their types, and hence can be considered as a superior approach when data available for training the system is abundant.

10aContext dependent and context independent data analysis10aFuzzy logic10aMLP10aNaive Bayesian classifier10aRandom Forest10aSocial networks10aTwitter1 aFazeen, Mohamed1 aDantu, Ram1 aGuturu, Parthasarathy uhttp://dx.doi.org/10.1007/s13278-011-0017-901811nas a2200265 4500008004100000245005300041210005300094260002700147520111600174653001301290653001401303653001401317653001001331653001101341653002201352653001701374653001801391653001801409653001201427653001601439100001801455700002001473700001501493856003701508 2011 eng d00aIndoor localization through dynamic time warping0 aIndoor localization through dynamic time warping aAnchorage, AKc10/20113 a

Identifying and locating oneself in different hallways of high rise buildings forms the classic indoor localization problem. GPS does not work indoors and WiFi may not be omnipresent. This paper presents a novel approach to ambient magnetic fields based indoor localization. We present a system that classifies magnetic signatures using dynamic time warping. Specifically, by aligning similar magnetic signatures that differ in magnitude or time, we classify the signatures and infer the location irrepective of the person and his/her mode of commuting. A Nexus One smartphone was employed, utilizing its builtin magnetic field sensor to create a user friendly localization application solely on the phone. By using a variety of subjects including sighted, blindfolded and people using wheelchairs to handle the human speed variation problem, we evaluated the system across 26 and 15 hallways of two different buildings and obtained accuracies of 92.6%, and 91.1% respectively. With these encouraging results, we believe our proposed solution is user independent and caters to a wide range of hallways.

10aAccuracy10aBuildings10aDatabases10aHuman10aHumans10aLegged locomotion10aLocalization10aMagnetometers10amobile phones10asensors10aWheelchairs1 aSubbu, Kalyan1 aGozick, Brandon1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/21602078nas a2200277 4500008004100000245004000041210004000081300001600121490000700137520135000144653001401494653003101508653003201539653002001571653001801591653002001609653001801629653001501647653001201662653001601674100002001690700001801710700001501728700002001743856003701763 2011 eng d00aMagnetic Maps for Indoor Navigation0 aMagnetic Maps for Indoor Navigation a3883 - 38910 v603 a

Magnetic field fluctuations and anomalies inside buildings tend to have a great effect on the compass, which is one of the simplest navigation devices. Alternative navigation requires landmark identification, so those landmarks can be used as guideposts in assisting individuals. By employing a mobile phone with built\_in magnetometer, an extensive data set of 2000 measurements was collected. Using these fields, we identify landmarks and guideposts and create magnetic maps for multiple corridors of a floor in a building. Different phones are used at different sensitivity rates, which effectively portray similar results. Magnetic signatures are used for identifying locations and rooms and are independent of the person, the phone, and the sensitivity of the sensor being used. Magnetic field behavior is demonstrated and compared with theoretical distributions of these fields. The developed magnetic maps can complement existing visual maps for location tracking and navigation of autonomous robots indoors. These maps are particularly useful during limited visual feedback in poor lighting conditions. Moreover, building designers could include this landmark and guidepost information when developing the architecture of a building, which could in turn help people or robots navigate during disasters and emergency evacuations.

10aBuildings10aMagnetic field measurement10aMagnetic field measurements10aMagnetic fields10aMagnetometers10aMobile handsets10amobile phones10aNavigation10asensors10aUncertainty1 aGozick, Brandon1 aSubbu, Kalyan1 aDantu, Ram1 aMaeshiro, Tomyo uhttps://nsl.cse.unt.edu/node/21101375nas a2200145 4500008004100000022001400041245004800055210004800103300001200151490000700163520096800170100002801138700001501166856004801181 2011 eng d a0951-566600aMobile Social Group Sizes and Scaling Ratio0 aMobile Social Group Sizes and Scaling Ratio a71–850 v263 a

Social data mining has become an emerging area of research in information and communication technology fields. The scope of social data mining has expanded significantly in the recent years with the advance of telecommunication technologies and the rapidly increasing accessibility of computing resources and mobile devices. People increasingly engage in and rely on phone communications for both personal and business purposes. Hence, mobile phones become an indispensable part of life for many people. In this article, we perform social data mining on mobile social networking by presenting a simple but efficient method to define social closeness and social grouping, which are then used to identify social sizes and scaling ratio of close to “8”. We conclude that social mobile network is a subset of the face-to-face social network, and both groupings are not necessary the same, hence the scaling ratios are distinct. Mobile social data mining.

1 aPhithakkitnukoon, Santi1 aDantu, Ram uhttp://dx.doi.org/10.1007/s00146-009-0230-502849nas a2200505 4500008004100000022001400041245007600055210006900131260000800200300001400208490000700222520128300229653003501512653001801547653002601565653001601591653003201607653002601639653003601665653001101701653000901712653004201721653002001763653001601783653003301799653002201832653001901854653001701873653001801890653002801908653002801936653003101964653002001995653002402015653002502039653003002064653001502094653002502109653002302134653003002157100001702187700001502204700002002219856010402239 2011 eng d a1083-442700aSocioscope: Human Relationship and Behavior Analysis in Social Networks0 aSocioscope Human Relationship and Behavior Analysis in Social Ne cNov a1122-11430 v413 a

In this paper, we propose a socioscope model for social-network and human-behavior analysis based on mobile-phone call-detail records. Because of the diversity and complexity of human social behavior, no one technique will detect every attribute that arises when humans engage in social behaviors. We use multiple probability and statistical methods for quantifying social groups, relationships, and communication patterns and for detecting human-behavior changes. We propose a new index to measure the level of reciprocity between users and their communication partners. This reciprocity index has application in homeland security, detection of unwanted calls (e.g., spam), telecommunication presence, and product marketing. For the validation of our results, we used real-life call logs of 81 users which contain approximately 500 000 h of data on users' location, communication, and device-usage behavior collected over eight months at the Massachusetts Institute of Technology (MIT) by the Reality Mining Project group. Also, call logs of 20 users collected over six months by the University of North Texas (UNT) Network Security team are used. The MIT and UNT data sets contain approximately 5000 callers. The experimental results show that our model is effective.

10abehavioural sciences computing10aChange points10acommunication pattern10aData models10ahuman relationship analysis10ahuman social behavior10ahuman-behavior change detection10aHumans10aIEEE10aMassachusetts Institute of Technology10aMobile handsets10aprobability10aReality Mining Project group10areciprocity index10aSocial factors10asocial group10asocial groups10asocial network analysis10aSocial network services10asocial networking (online)10aSocial networks10asocial relationship10asocial relationships10asocial sciences computing10asocioscope10aStatistical analysis10astatistical method10aUniversity of North Texas1 aZhang, Huiqi1 aDantu, Ram1 aCangussu, João uhttps://nsl.cse.unt.edu/content/socioscope-human-relationship-and-behavior-analysis-social-networks01210nas a2200145 4500008004100000022001400041245005400055210005400109300001200163490000700175520079200182100002800974700001501002856004701017 2011 eng d a1559-166200aTowards Ubiquitous Computing with Call Prediction0 aTowards Ubiquitous Computing with Call Prediction a52–640 v153 a

With the long-awaited era of the pervasive computing approaches, the handheld devices such as personal mobile phones begin to evolve into ubiquitous computing devices. At this early stage of the evolution, we propose a model of a call predictor based on the naive Bayesian classifier. As an incoming call predictor, our model makes use of the user’s call history to generate a list of numbers/contacts that are the most likely to be the callers within the next hour. On the other hand, when the user wants to make an outgoing call (e.g., user flips open the phone or unlocks the phone, etc.), the outgoing call predictor generates a list of number/contacts to be called. Our model has been evaluated with the real-life call logs and it shows a promising result in accuracy.

1 aPhithakkitnukoon, Santi1 aDantu, Ram uhttp://doi.acm.org/10.1145/1978622.197862801984nas a2200349 4500008004100000245005500041210005500096260000800151520101900159653002601178653001601204653002301220653001701243653001301260653002001273653001301293653001901306653001901325653002701344653001601371653001201387653003101399653002901430653002101459653001201480653001901492653001501511653002801526100002801554700001501582856003701597 2011 eng d00aUnveiling Hidden Patterns to Find Social Relevance0 aUnveiling Hidden Patterns to Find Social Relevance cOct3 a

Twitter is both a useful social networking device and an incredible marketing tool. However, it is also a venue for dangerous stalkers and a sub-world of internet users that most people would intuitively avoid if seeing them in real life. It would improve Twitter's safety to have filters available which would allow users to select an audience for their status updates without being forced into changing their profiles to a private setting. The hypothetical filter, or model, studied in this paper was based on two particular attributes: activity correlations and vocabulary similarities between users and followers. If implemented, this model would restrict the availability of status updates to an automatically generated group of socially relevant followers. The result of this study shows that both of the attributes can be used to define social relevance, however, it was found that activity patterns have better predictive capabilities than correlating vocabulary usage between users and followers.

10aactivity correlations10aCorrelation10adangerous stalkers10adata privacy10aFacebook10ahidden patterns10aInternet10aInternet users10amarketing tool10aOnline Social Networks10aPolynomials10aPrivacy10asocial networking (online)10asocial networking device10asocial relevance10aTwitter10aTwitter safety10aVocabulary10avocabulary similarities1 aBaatarjav, Enkh-Amgalan1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/23801677nas a2200193 4500008004100000020002200041245002300063210002200086260003600108520114900144653002601293653001201319653001201331100002801343700001901371700001501390700002401405856005401429 2010 eng d a978-1-4244-5175-300aAre You My Friend?0 aAre You My Friend aPiscataway, NJ, USAbIEEE Press3 a

With Twitters growing popularity, privacy has become a major concern for users wary of sensitive information falling in the wrong hands. A typical Twitter user carries hundreds of followers - people who have subscribed to users twitter feeds. Our goal is to target followers that a Twitter user deems safe. Therefore, selecting followers with a closer relationship could help decrease the risk of sensitive information being sent to unknown people. We propose a privacy management system that helps a Twitter user restrict information to only certain followers based on the strength of their social tie. This system would incorporate two tools: the Exclusivity meter and the Twitter Response Estimator. The Exclusivity Meter employs user’s activity profile to guess similarities between users. Preliminary results have indicated that similarity in time and level of activity between user and follower does suggest a stronger social tie. The Twitter Response Estimator uses a measure of prestige to gauge the probability of response. When applied to a set of followers, the estimator separates real friends from recreational followers

10aonline social network10aPrivacy10aTwitter1 aBaatarjav, Enkh-Amgalan1 aAmin, Aliasgar1 aDantu, Ram1 aGupta, Nikhil, Kant uhttp://dl.acm.org/citation.cfm?id=1834217.183434202408nas a2200157 4500008004100000022001400041245006400055210006300119260000800182300001100190490000600201520196300207100002802170700001502198856003702213 2010 eng d a1742-737100aContextAlert: Context‐aware alert mode for a mobile phone0 aContextAlert Context‐aware alert mode for a mobile phone cSep a1–230 v63 a

Purpose – Mobile computing research has been focused on developing technologies for handheld devices such as mobile phones, notebook computers, and mobile IP. Today, emphasis is increasing on context-aware computing, which aims to build the intelligence into mobile devices to sense and respond to the user’s context. The purpose of this paper is to present a context-aware mobile computing model (ContextAlert) that senses the user’s context and intelligently configures the mobile phone alert mode accordingly. Design/methodology/approach – The paper proposes a three-step approach in designing the model based on the embedded sensor data (accelerometer, GPS antenna, and microphone) of a G1 Adriod phone. As adaptivity is essential for context-aware computing, within this model a new learning mechanism is presented to maintain a constant adaptivity rate for new learning while keeping the catastrophic forgetting problem minimal. Findings – The model has been evaluated in many aspects using data collected from human subjects. The experiment results show that the proposed model performs well and yields a promising result. Originality/value – This paper is distinguished from other previous papers by: first, using multiple sensors embeded in the mobile phone, which is more realistic for detecting the user’s context than having various sensors attached to different parts of user’s body; second, by being a novel model that uses sensed contextual information to provide a service that better synchronizes the user’s daily life with a context-aware alert mode. With this service, the user can avoid the problems such as forgetting to switch to vibrate mode while in a meeting or a movie theater, and taking the risk of picking up a phone call while driving, and third, being an adaptive learning algorithm that maintains a constant adaptivity rate for new learning while keeping the catastrophic forgetting problem minimal.

1 aPhithakkitnukoon, Santi1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/22100691nas a2200205 4500008004100000020002200041245007100063210006900134260003600203653001600239653002100255653002000276653003300296100002700329700001500356700001800371700001800389700002400407856005400431 2010 eng d a978-1-4244-5487-700aEfficiency of Social Connection-based Routing in P2P VoIP Networks0 aEfficiency of Social Connectionbased Routing in P2P VoIP Network aPiscataway, NJ, USAbIEEE Press10aP2P routing10aP2P VoIP systems10aSocial networks10asocial-network based routing1 aChandrasekaran, Vikram1 aDantu, Ram1 aGupta, Neeraj1 aYang, Xiaohui1 aWijesekera, Duminda uhttp://dl.acm.org/citation.cfm?id=1831443.183148801492nas a2200217 4500008004100000020002200041245002500063210002500088260005100113300001200164520088400176100001701060700002801077700001501105700002001120700001801140700002601158700002801184700001201212856005001224 2010 eng d a978-3-642-11322-200aEmail Shape Analysis0 aEmail Shape Analysis aBerlin, HeidelbergbSpringer Berlin Heidelberg a18–293 a

Email has become an integral part of everyday life. Without a second thought we receive bills, bank statements, and sales promotions all to our inbox. Each email has hidden features that can be extracted. In this paper, we present a new mechanism to characterize an email without using content or context called Email Shape Analysis. We explore the applications of the email shape by carrying out a case study; botnet detection and two possible applications: spam filtering, and social-context based finger printing. Our in-depth analysis of botnet detection leads to very high accuracy of tracing templates and spam campaigns. However, when it comes to spam filtering we do not propose new method but rather a complementing method to the already high accuracy Bayesian spam filter. We also look at its ability to classify individual senders in personal email inbox’s.

1 aSroufe, Paul1 aPhithakkitnukoon, Santi1 aDantu, Ram1 aCangussu, João1 aKant, Krishna1 aPemmaraju, Sriram, V.1 aSivalingam, Krishna, M.1 aWu, Jie uhttp://dx.doi.org/10.1007/978-3-642-11322-2_701299nas a2200205 4500008004100000245006200041210006200103300001400165490000600179520071400185653003000899653002700929653002200956653001200978100001700990700001601007700001501023700001801038856003701056 2010 eng d00aExperiences During a Collegiate Cyber Defense Competition0 aExperiences During a Collegiate Cyber Defense Competition a382–3960 v53 a

The objective of this article is to encourage schools to participate in the Collegiate Cyber Defense Competition (CCDC) and to ease their entry by providing information about the event and describing the experiences of both the student participants and the educators. This article focuses mainly on the recent experience of a University of North Texas student team at the Southwest Regional CCDC 2008 hosted by Del Mar College in Corpus Christi, Texas. It describes the entire process of participating in the CCDC, including announcements, team formation, task assignments, preparations, and actual team experience during the competition and provides suggestions on strategies for future competitions

10aCyber defense competition10anetwork configurations10aoperating systems10aservers1 aSroufe, Paul1 aTate, Steve1 aDantu, Ram1 aCankaya, Ebru uhttps://nsl.cse.unt.edu/node/14801135nas a2200133 4500008004100000020002200041245005500063210005500118260003600173520069500209100002800904700001500932856005400947 2010 eng d a978-1-4244-5175-300aMobile Social Closeness and Communication Patterns0 aMobile Social Closeness and Communication Patterns aPiscataway, NJ, USAbIEEE Press3 a

As mobile networks expand rapidly to facilitate the rising number of mobile phone population, more mobile social services are being developed and offered. To create an efficient social functionality, characteristics of mobile social network must be studied. Social closeness is one of the basic fundamentals of any kind of social networking. In this paper, closeness in mobile social network is the subject of the study, from which social grouping scheme is proposed and validated against the feedbacks of human subjects. Based on the proposed grouping scheme, a study of the impact of the mobile social closeness to the similarity in calling patterns and reciprocity is presented.

1 aPhithakkitnukoon, Santi1 aDantu, Ram uhttp://dl.acm.org/citation.cfm?id=1834217.183428501263nas a2200157 4500008004100000245010900041210006900150490000600219520074700225100001800972700001500990700002501005700001801030700002001048856003701068 2010 eng d00aNext generation 9-1-1: Architecture and challenges in realizing an IP-multimedia-based emergency service0 aNext generation 911 Architecture and challenges in realizing an 0 v73 a

Next generation 9-1-1 (NG-9-1-1) services will enable the use of multimedia (voice, video, text messages, and data) for emergency communications. This will be made possible using a whole new architecture for emergency communications, one that is based on the internet protocol (IP) and open standards. VOIP based communication services vastly improve the effectiveness of relief during mass disasters, as was observed during Katrina. However, delivering the latest multimedia technology to Public Service Answering Points (PSAPs) presents both new opportunities and challenges. In this paper, we review how technology is evolving towards an NG-9-1-1 solution and underscore the challenges and issues that still require investigation.

1 aGupta, Neeraj1 aDantu, Ram1 aSchulzrinne, Henning1 aGoulart, Anna1 aMagnussen, Walt uhttps://nsl.cse.unt.edu/node/13202097nas a2200217 4500008004100000020002200041245005200063210005200115260003500167520147400202653001001676653001501686653002201701653001801723653002001741653002501761653002401786100001701810700001501827856003701842 2010 eng d a978-1-4244-6444-900aPredicting social ties in mobile phone networks0 aPredicting social ties in mobile phone networks aVancouver, BC, Canadac05/20103 a

A social network dynamically changes since the social relationships (social ties) change over time. The evolution of a social network mainly depends on the evolution of the social relationships. The social-tie strengths of person-to-person are different one another even though they are in the same group. In this paper we investigate the evolution of person-to-person social relationships, quantify and predict social tie strengths based on call-detail records of mobile phones. We propose an affinity model for quantifying social-tie strengths in which a reciprocity index is integrated to measure the level of reciprocity between users and their communication partners. Since human social relationships change over time, we map the call-log data to time series of the social-tie strengths by the affinity model. Then we use ARIMA model to predict social-tie strengths. For validation of our results, we used actual call logs of 81 users collected for a period of 8 months at MIT by the Reality Mining Project group and also used call logs of 20 users collected for a period of 6 months by UNT's Network Security team. These users have around 5000 communication partners. The experimental results show that our model is effective. We achieve prediction performance with accuracy of average 95.2% for socially close and near members. Among other applications, this work is useful for homeland security, detection of unwanted calls (e.g., spam), and marketing.

10aARIMA10aPrediction10areciprocity index10asocial groups10aSocial networks10asocial relationships10aSocial-tie strength1 aZhang, Huiqi1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/14101834nas a2200289 4500008004100000020002200041245002100063210002100084260005100105300001400156520110600170653001401276653001301290653001301303653001301316653001701329653001201346653001601358653000901374100001801383700002101401700001501422700002401437700001701461700001601478856005001494 2010 eng d a978-3-642-29336-800aSmall World VoIP0 aSmall World VoIP aBerlin, HeidelbergbSpringer Berlin Heidelberg a137–1553 a

We present the analysis and design of a Small World VoIP system (SW-VoIP) which is geared towards customers that are communicating with their Small World of social contacts. We use the term Small World to refer to the Peer-to-Peer (P2P) network of a client and his contacts both incoming and outbound. We reconstruct the small world of a user by collecting calling patterns over a configurable period of time. We enable user mobility by using a stepwise social identity to an IP address binding propagation model. We propose an efficient algorithm to locate users by electing popular users and leveraging the users closeness. We also introduce a self-stabilized load balancing mechanism to optimize the system performance under heavy network traffic. We evaluate our SW-VoIP system performance by simulating the user’s lookup process using real-world telephone logs. Our experimental results show that our SW-VoIP system offers a better performance in optimizing the required routing path and reducing the average lookup delay when compared to traditional, non small-world P2P VoIP systems.

10acloseness10aelecting10amobility10aoptimize10aPeer-to-peer10apopular10asmall world10aVoIP1 aYang, Xiaohui1 aStavrou, Angelos1 aDantu, Ram1 aWijesekera, Duminda1 aGris, Martin1 aYang, Guang uhttp://dx.doi.org/10.1007/978-3-642-29336-8_802337nas a2200133 4500008004100000020002200041245008300063210006900146260004700215520187200262100001702134700001502151856003702166 2010 eng d a978-1-124-36491-900aSocioscope: Human Relationship and Behavior Analysis in Mobile Social Networks0 aSocioscope Human Relationship and Behavior Analysis in Mobile So aDenton, TX, USAbUniversity of North Texas3 a

The widely used mobile phone, as well as its related technologies had opened opportunities for a complete change on how people interact and build relationship across geographic and time considerations. The convenience of instant communication by mobile phones that broke the barrier of space and time is evidently the key motivational point on why such technologies so important in people’s life and daily activities. Mobile phones have become the most popular communication tools.

Mobile phone technology is apparently changing our relationship to each other in our work and lives. The impact of new technologies on people's lives in social spaces gives us the chance to rethink the possibilities of technologies in social interaction. Accordingly, mobile phones are basically changing social relations in ways that are intricate to measure with any precision.

In this dissertation I propose a socioscope model for social network, relationship and human behavior analysis based on mobile phone call detail records. Because of the diversities and complexities of human social behavior, one technique cannot detect different features of human social behaviors. Therefore I use multiple probability and statistical methods for quantifying social groups, relationships and communication patterns, for predicting social tie strengths and for detecting human behavior changes and unusual consumption events. I propose a new reciprocity index to measure the level of reciprocity between users and their communication partners. The experimental results show that this approach is effective. Among other applications, this work is useful for homeland security, detection of unwanted calls (e.g., spam), telecommunication presence, and marketing. In my future work I plan to analyze and study the social network dynamics and evolution.

1 aZhang, Huiqi1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/14002615nas a2200457 4500008004100000245004400041210004300085260000800128520134600136653001401482653001201496653001101508653002101519653002301540653003101563653001401594653003301608653001901641653002401660653001801684653002801702653003301730653002701763653002001790653002101810653001701831653001701848653001701865653001801882653002001900653002301920653001601943653001901959653003301978100002702011700001602038700002302054700001502077700002802092856003702120 2010 eng d00aSocio-technical aspects of video phones0 aSociotechnical aspects of video phones cJan3 a

The widespread use of voice over Internet protocol has paved the way for video over Internet protocol. In the past, certain technical shortcomings have prevented the popularity of videophones in the market. With present-day technology, videophones have just about everything required for day-to-day functions. Under such circumstances, certain socio-technical aspects require attention so that videophones can become as widespread and as technically streamlined as a plain old telephone system (POTS) with its additional benefits. A frequently brushed-upon topic is optimum features in the video phone for day-to-day social interactions. We carried out several experiments on different kinds of codecs and video formats to address two issues: i) the size of a video screen and ii) perception of motion and distance. From the measurements, we observed that a small frame rate with low bandwidth is adequate and can result in satisfactory video quality. We also observed that H263 performs well for all the day-to-day social networking activities. Standing 4 feet from the camera can still give reasonably good video quality in the currently available codecs. We believe that socio-technical issues will emerge more clearly over the next several years and they are germane to deployment of PC-based soft phones as well as hard phones.

10aBandwidth10aCameras10aCodecs10aComputer science10aInternet telephony10aplain old telephone system10aProtocols10asocial aspects of automation10aSocial factors10asocial interactions10asocial issues10aSocial network services10asocial networking activities10asociotechnical aspects10aStreaming media10atechnical issues10avideo codecs10avideo coding10avideo phones10avideo quality10aVideoconference10avideophone quality10avideophones10avideotelephony10avoice over Internet protocol1 aChandrasekaran, Vikram1 aDantu, Siva1 aKadiyala, Priyanka1 aDantu, Ram1 aPhithakkitnukoon, Santi uhttps://nsl.cse.unt.edu/node/17000370nas a2200121 4500008004100000245005400041210005300095300000800148100002000156700001500176700002000191856003700211 2010 eng d00aSpam Classification Based on E-Mail Path Analysis0 aSpam Classification Based on EMail Path Analysis a3321 aPalla, Srikanth1 aDantu, Ram1 aCangussu, João uhttps://nsl.cse.unt.edu/node/17701302nas a2200313 4500008004100000022001400041245006000055210005800115300001200173490000600185520045000191653002200641653002600663653002100689653001900710653001200729653001300741653002300754653001200777653001600789653002100805653001200826653002300838100002000861700001900881700002400900700001500924856004900939 2010 eng d a1748-127900aA Testbed for Large Mobile Social Computing Experiments0 aTestbed for Large Mobile Social Computing Experiments a89–970 v83 a

We present a testbed for mobile social computing that can be used to perform research in security, privacy and context-awareness policies and mechanisms appropriate for a wide range of applications. We compare several mobile platforms and present the rational for our design choices and reasons we chose Android as the primary smartphone for the testbed. We also discuss some of the experiments that can be conducted using this testbed.

10acontext awareness10amobile communications10amobile computing10amobile devices10aPrivacy10aSecurity10asensor information10asensors10asmartphones10asocial computing10atestbed10aubiquitous devices1 aAlazzawe, Ahmed1 aAlazzawe, Anis1 aWijesekera, Duminda1 aDantu, Ram uhttp://dx.doi.org/10.1504/IJSNET.2010.03461801762nas a2200145 4500008004100000020002200041245007700063210006900140260003600209520126000245100001801505700001501523700002401538856005401562 2009 eng d a978-1-4244-2308-800aAchieving Peer-to-peer Telecommunication Services Through Social Hashing0 aAchieving Peertopeer Telecommunication Services Through Social H aPiscataway, NJ, USAbIEEE Press3 a

Although peer-to-peer (P2P) Internet Telephony gains more and more market share, supporting traditional telephony related use cases is an indispensable requirement. However, communication services designed for this purpose are usually traditional circuit-based, and the centralized structure makes it nearly impossible for their deployments in a distributed, unsecure telecommunication environment. This paper proposes an approach for achieving various kinds of communication services on P2P voice over IP (VoIP) systems by building trust and executing supervision through social networks. We present a system architecture design for network topology maintenance and security assurance. Social protocols and social computing are used to study how P2P entities can be efficiently mapped to social networks, and how social functionalities can benefit communication services implementation. To demonstrate the approach feasibility, we exemplify this architecture in P2P VoIP emergency services by using gossiping and membership management techniques. We believe that our proposed approach will be able to support diverse services on P2P VoIP systems with the performance and security guaranteed to compete with centralized telecommunication systems.

1 aYang, Xiaohui1 aDantu, Ram1 aWijesekera, Duminda uhttp://dl.acm.org/citation.cfm?id=1700527.170058200372nas a2200109 4500008004100000245007000041210006600111300000700177100001500184700002600199856003700225 2009 eng d00aAn Architecture for IP-based Next Generation Radio Access Network0 aArchitecture for IPbased Next Generation Radio Access Network a611 aDantu, Ram1 aGuturu, Parthasarathy uhttps://nsl.cse.unt.edu/node/12201602nas a2200229 4500008004100000020002200041245002700063210002600090260004700116520102300163653001801186653001201204653001201216653001401228653001701242653001601259653000901275653001101284100001901295700001501314856004301329 2009 eng d a978-0-7695-3823-500aAre You a Safe Driver?0 aAre You a Safe Driver aWashington, DC, USAbIEEE Computer Society3 a

As the world continues to enhance and strengthen its emergency services, mobile phones may be used to aid in safe driving practices and detection of emergencies. To our knowledge, no work has been reported in understanding vehicle motion using accelerometers/compass in cell phones. In this paper, we used the multiple sensors in a Google phone to classify safe versus unsafe driving. In particular, we used breaking distance, acceleration, and deceleration for detecting safe verses unsafe braking. Next, we calculated the displacement in the axis perpendicular to the trajectory of vehicle and used it to classify safe and unsafe lane changes. The direction of the phone with respect to the motion of the vehicle is important during calibration of the above measurements, so we used 2D and 3D rotation matrices for transforming device orientation. Future work includes calibration of braking distance, lane changes, and reliable transformation of phone orientation with respect to trajectory of the vehicle.

10aAccelerometer10aAndroid10adriving10aemergency10amobile phone10aorientation10asafe10aunsafe1 aLangle, Lonnie1 aDantu, Ram uhttp://dx.doi.org/10.1109/CSE.2009.33101439nas a2200157 4500008004100000020002200041245005300063210005200116260003600168520094600204100002801150700001501178700001401193700002001207856005401227 2009 eng d a978-1-4244-4171-600aBBN-based Privacy Management System for Facebook0 aBBNbased Privacy Management System for Facebook aPiscataway, NJ, USAbIEEE Press3 a

Online social networking sites (SNSs) has changed our lifestyle and become a main medium of communication among young adults to stay in touch with their friends, to organize events, to make friends, to promote themselves, to date, etc. To create content rich environment, SNSs make their platform available for third-party developers. The developers can build their applications based on users' social graph containing their personal and social information. Unfortunately, any information users posted on their profile can be harvested and used for unethical purposes due to Facebook's lack of application privacy configuration. In this paper we propose a privacy-management system for Facebook applications. The system can take advantage of the correlation between some profile features and network privacy settings, in this way it can automatically configure a users privacy settings. Our preliminary result show promising result.

1 aBaatarjav, Enkh-Amgalan1 aDantu, Ram1 aTang, Yan1 aCangussu, João uhttp://dl.acm.org/citation.cfm?id=1706428.170646701172nas a2200145 4500008004100000020002200041245005600063210005600119260003600175520070900211100001700920700001500937700002000952856005400972 2009 eng d a978-1-4244-4171-600aChange Point Detection Based on Call Detail Records0 aChange Point Detection Based on Call Detail Records aPiscataway, NJ, USAbIEEE Press3 a

In this paper we propose a method for combining wavelet denoising and sequential approach for detecting change points on mobile phone based on detailed call records. The Minmax method is used to estimate the thresholds of frequency and call duration for denoising. This work is useful to enhance homeland security, detecting unwanted calls (e.g., spam) and commercial purposes. For validation of our results, we randomly choose actual call logs of 20 users from 100 users collected at MIT by the Reality Mining Project group for a period of 8 months. Simulation data is also used to validate the results. The experimental results show that our model achieves good performance with high accuracy.

1 aZhang, Huiqi1 aDantu, Ram1 aCangussu, João uhttp://dl.acm.org/citation.cfm?id=1706428.170643800836nas a2200133 4500008004100000020002200041245004900063210004900112260003600161520040800197100002800605700001500633856005400648 2009 eng d a978-1-4244-4171-600aDefense Against SPIT Using Community Signals0 aDefense Against SPIT Using Community Signals aPiscataway, NJ, USAbIEEE Press3 a

Internet telephony has recently gained popularity. Voice over IP (VoIP) has emerged as an alternative to the current public switched telephone network (PSTN) system due to its cost efficiency. Spam inherently becomes a problem in VoIP networks. In this paper, we present our ongoing research in defending VoIP networks against spam by presenting a new defense mechanism using community signals.

1 aPhithakkitnukoon, Santi1 aDantu, Ram uhttp://dl.acm.org/citation.cfm?id=1706428.170648101311nas a2200157 4500008004100000020002200041245005100063210005100114260003600165520081800201100001701019700002801036700001501064700002001079856005401099 2009 eng d a978-1-4244-2308-800aEmail Shape Analysis for Spam Botnet Detection0 aEmail Shape Analysis for Spam Botnet Detection aPiscataway, NJ, USAbIEEE Press3 a

Botnets have become the major sources of spamming, which generates massive unwanted traffic on networks. An effective detection mechanism can greatly mitigate the problem. In this paper, we present a novel botnet detection mechanism based on the email "shape" analysis that relies on neither content nor reputation analysis. Shape is our new way of characterizing an email by mimicking human visual inspection. A set of email shapes are derived and then used to generate a botnet signature. Our preliminary results show greater than 80% classification accuracy (without considering email content or reputation analysis). This work investigates the discriminatory power of email shape, for which we believe will be a significant complement to other existing techniques such as a network behavior analysis.

1 aSroufe, Paul1 aPhithakkitnukoon, Santi1 aDantu, Ram1 aCangussu, João uhttp://dl.acm.org/citation.cfm?id=1700527.170079200380nas a2200133 4500008004100000020002200041245002400063210002400087260004700111100001800158700001300176700001500189856004200204 2009 eng d a978-0-7695-3823-500aiKnow Where You Are0 aiKnow Where You Are aWashington, DC, USAbIEEE Computer Society1 aSubbu, Kalyan1 aXu, Ning1 aDantu, Ram uhttp://dx.doi.org/10.1109/CSE.2009.5501214nas a2200217 4500008004100000245004300041210004300084300001200127490000700139520065300146653001300799653002300812653001200835653001700847653001800864100001500882700001700897700002500914700002000939856003700959 2009 eng d00aIssues and challenges in securing VoIP0 aIssues and challenges in securing VoIP a743-7530 v283 a

Voice over the Internet protocol (VoIP) is being rapidly deployed, and the convergence of the voice and data worlds is introducing exciting opportunities. Lower cost and greater flexibility are the key factors luring enterprises to transition to VoIP. Some security problems may surface with the widespread deployment of VoIP. In this article, we discuss these security problems and propose a high-level security architecture that captures required features at each boundary-network-element in the VoIP infrastructure. We describe mechanisms to efficiently integrate information between distributed security components in the architecture.

10aFeedback10aSecurity solutions10aThreats10aVoIP attacks10aVoIP security1 aDantu, Ram1 aFahmy, Sonia1 aSchulzrinne, Henning1 aCangussu, João uhttps://nsl.cse.unt.edu/node/19900990nas a2200193 4500008004100000245006400041210006400105260003800169520043200207653000900639653001100648653000900659653001200668653000900680100001800689700001500707700002100722856005300743 2009 eng d00aMethod and system for managing wireless bandwidth resources0 aMethod and system for managing wireless bandwidth resources aUSbCisco Technology Incc05/20093 a

A method and system for managing wireless bandwidth resources include the capability to receive at a serving node a service request for a mobile unit and to communicate with a wireless network node to determine whether sufficient wireless bandwidth is available for the requested service. The method and system also include the capability to process the service request based on the availability of wireless bandwidth.

10adata10amobile10anode10aservice10aunit1 aHolur, Balaji1 aDantu, Ram1 aDerrick, Charles uhttps://patents.google.com/patent/US7539499B2/en01285nas a2200205 4500008004100000245009300041210006900134260003800203520066500241653001000906653000900916653000800925653001100933653001200944100001500956700002100971700001700992700001901009856005101028 2009 eng d00aMethod and system for providing wireless-specific services for a wireless access network0 aMethod and system for providing wirelessspecific services for a  aUSbCisco Technology Incc12/20093 a

A method and system for providing wireless-specific services for a wireless access network includes receiving at a call agent of a wireless access network a call origination for a mobile device. Whether the device is registered on the wireless access network is determined. If the mobile device is not registered, whether the mobile device is active is determined at a mobility control function (MCF). If the mobile device is active, the call is connected to the mobile device with a call agent based on a temporary line directory number (TLDN) assigned by the MCF and passed to the call agent in an extended session initiation protocol (SIP) message.

10aagent10acall10amcf10amobile10anetwork1 aDantu, Ram1 aChiang, Shihlung1 aYin, Haochih1 aKachhla, Rasik uhttps://patents.google.com/patent/US7639647/en01794nas a2200193 4500008004100000022001400041245005300055210005300108300001200161490000600173520127900179653001801458653001301476653002001489100001501509700001901524700002001543856003701563 2009 eng d a1939-012200aNetwork risk management using attacker profiling0 aNetwork risk management using attacker profiling a83–960 v23 a

Risk management refers to the process of making decisions that minimize the effects of vulnerabilities on the network hosts. This can be a difficult task in the context of high-exploit probability and the difficult to identify new exploits and vulnerabilities. For many years, security engineers have performed risk analysis using economic models for the design and operation of risk-prone, technological systems using attack profiles. Based on the type of attacker identified, security administrators can formulate effective risk management policies for a network. We hypothesize that sequence of network actions by an attacker depends on the social behavior (e.g., skill level, tenacity, financial ability). We extended this and formulated a mechanism to estimate the risk level of critical resources that may be compromised based on attacker behavior. This estimation is accomplished using behavior based attack graphs representing all the possible attack paths to all the critical resources. The risk level is computed based on these graphs and are used as a measure of the vulnerability of the resource and forming an effective basis for a system administrator to perform suitable changes to network configuration. Copyright © 2008 John Wiley & Sons, Ltd.

10aattack graphs10abehavior10arisk management1 aDantu, Ram1 aKolan, Prakash1 aCangussu, João uhttp://dx.doi.org/10.1002/sec.5801020nas a2200133 4500008004100000020002200041245005000063210004900113260003500162520060300197100001700800700001500817856005400832 2009 eng d a978-1-4244-2308-800aOpt-in Detection Based on Call Detail Records0 aOptin Detection Based on Call Detail Records aLas Vegas, NV, USAbIEEE Press3 a

Opt-in phone calls or emails refer to promotional phone calls or emails that have been requested by the people receiving them. In this paper we propose a model based on dynamic sliding windows to detect opt-in phone calls based on mobile phone call detail records. This work is useful for detecting unwanted calls (e.g., spam) and commercial purposes. For validation of our results, we used actual call logs of 100 users collected at MIT by the Reality Mining Project group for a period of 8 months. The experimental results show that our model achieves good performance with 91% accuracy.

1 aZhang, Huiqi1 aDantu, Ram uhttp://dl.acm.org/citation.cfm?id=1700527.170069001170nas a2200181 4500008004100000020002200041245004100063210004100104260003900145520064000184653002100824653002400845653001600869100002100885700002000906700001500926856004700941 2009 eng d a978-0-7695-3726-900aPenetration Testing for Spam Filters0 aPenetration Testing for Spam Filters aSeattle, WAbIEEE Computer Society3 a

Despite all the advances on techniques to block spam e-mail messages we still receive them on a frequent basis. This is due mainly to the ability of the spammers to modify the message and pass the filters. Therefore a testing technique that could resemble the behavior of spammers would improve the number of scenarios tested and allow filters to be developed based on the potential changes made by the spammers. An approach based on Natural Language Processing (NLP) for the penetration of spam filters is proposed here. Preliminary results using SpamAssassin are provided indicating the feasibility of the proposed approach.

10amutation testing10apenetration testing10aspam filter1 aMadhavan, Yugesh1 aCangussu, João1 aDantu, Ram uhttp://dx.doi.org/10.1109/COMPSAC.2009.16801104nas a2200145 4500008004100000020002200041245004700063210004700110260004700157520065900204100001700863700001500880700002000895856004300915 2009 eng d a978-0-7695-3823-500aQuantifying Reciprocity in Social Networks0 aQuantifying Reciprocity in Social Networks aWashington, DC, USAbIEEE Computer Society3 a

In this paper we propose a new reciprocity index for quantifying social relationships based on mobile phone call detail records and Twitter blogs. We use this reciprocity index to measure the level of reciprocity between users. This work is useful for detecting unwanted calls (e.g., spam) and product marketing. For validation of our results, we used actual call logs of 100 users collected at MIT by the Reality Mining Project group for a period of 8 months and Twitter blogs of 460 users collected by the Network Security team at UNT for a period of 12 months. The experimental results show that our model achieves results with high accuracy.

1 aZhang, Huiqi1 aDantu, Ram1 aCangussu, João uhttp://dx.doi.org/10.1109/CSE.2009.39901985nas a2200373 4500008004100000245008200041210006900123260001000192520080200202653002601004653002101030653002201051653002101073653001301094653002201107653002301129653002001152653002201172653002701194653002701221653004301248653003301291653002201324653002801346653004401374653002601418653003101444653003001475653001201505100001801517700001501535700002401550856003701574 2009 eng d00aA society-integrated testbed architecture for peer-to-peer telecommunications0 asocietyintegrated testbed architecture for peertopeer telecommun cApril3 a

Exploiting and deploying telecommunication services on Internet Telephony are imperative for a large market share. However, the distributed nature of peer-to-peer (P2P) network makes services implementation very difficult. In order to meet the research goals of achieving P2P telecommunication services through the union of social and computer networks, we present a society-integrated testbed architecture for P2P voice over IP (VoIP). By introducing an architecture that exploits and entailing social structure based connection establishment, the testbed presents an organic integration of social functionalities with good portability. The testbed also serves as a flexible tool suite that can be used to run experiments and obtain timely feedback based on the performance measurements.

10aComputer architecture10acomputer network10acomputer networks10aComputer science10aFeedback10afile organisation10aInternet telephony10anetwork traffic10aP2P voice-over-IP10aPeer to peer computing10apeer-to-peer computing10apeer-to-peer telecommunication service10aportable social DHT function10aRouting protocols10aSocial network services10asociety-integrated testbed architecture10asoftware architecture10aTelecommunication services10atelecommunication traffic10aTesting1 aYang, Xiaohui1 aDantu, Ram1 aWijesekera, Duminda uhttps://nsl.cse.unt.edu/node/23901387nas a2200337 4500008004100000245004200041210004000083260001000123520046000133653002100593653002100614653002200635653002900657653001700686653001300703653003000716653002100746653002800767653002700795653001200822653001900834653002100853653002000874653002800894653001200922100002000934700001900954700002400973700001500997856003701012 2009 eng d00aA testbed for mobile social computing0 atestbed for mobile social computing cApril3 a

We present a testbed for mobile social computing that can be used to perform research in security, privacy, and context-awareness policies and mechanisms appropriate for a wide range of applications. We compare several mobile platforms and present the rational for our design choices and reasons we chose Android as the primary smartphone for this testbed. We also discuss some of the possible experiments that can be conducted using the testbed.

10aAcoustic sensors10aComputer science10aComputer security10acontext-awareness policy10adata privacy10aFeedback10aGlobal Positioning System10amobile computing10amobile social computing10aPerformance evaluation10aPrivacy10aprivacy policy10asecurity of data10asecurity policy10aSocial network services10aTesting1 aAlazzawe, Ahmed1 aAlazzawe, Anis1 aWijesekera, Duminda1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/22701359nas a2200193 4500008004100000022001400041245004600055210004400101300001400145490000700159520083700166653002101003653002101024653002001045100001601065700002001081700001501101856004901116 2009 eng d a1084-804500aA Virtual Environment for Network Testing0 aVirtual Environment for Network Testing a184–2140 v323 a

The testing of network-based solutions demands a series of tedious tasks such as the deployment of the solution at different nodes and the configuration of different topologies. The manual execution of these tasks is very time consuming and a configurable environment to facilitate these tasks and consequently improve testing performance is desired. In this paper a virtual network environment that can be easily re-configured is presented to address this problem. The environment has been evaluated by a series of case studies: one dealing with the deployment and containment of a worm propagation attack and one dealing with detecting a denial of service attack. Three smaller case studies have also been developed. The results are a clear indication of the flexibility and usefulness of the virtual network environment.

10aRe-configuration10aSoftware testing10aVirtual network1 aFagen, Wade1 aCangussu, João1 aDantu, Ram uhttp://dx.doi.org/10.1016/j.jnca.2008.03.00800331nas a2200097 4500008004100000245005600041210005600097100002800153700001500181856003700196 2008 eng d00aAdequacy of data for characterizing caller behavior0 aAdequacy of data for characterizing caller behavior1 aPhithakkitnukoon, Santi1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/16902279nas a2200373 4500008004100000245003800041210003800079520122200117653003001339653001201369653003001381653002501411653002601436653001601462653002001478653001601498653001401514653002601528653002201554653002101576653002701597653002301624653000801647653003301655653001901688653002801707653002301735653002901758100001801787700002801805700002001833700001501853856003701868 2008 eng d00aBehavior analysis of spam botnets0 aBehavior analysis of spam botnets3 a

Compromised computers, known as bots, are the major source of spamming and their detection helps greatly improve control of unwanted traffic. In this work we investigate the behavior patterns of spammers based on their underlying similarities in spamming. To our knowledge, no work has been reported on identifying spam botnets based on spammerspsila temporal characteristics. Our study shows that the relationship among spammers demonstrates highly clustering structures based on features such as content length, time of arrival, frequency of email, active time, inter-arrival time, and content type. Although the dimensions of the collected feature set is low, we perform principal component analysis (PCA) on feature set to identify the features which account for the maximum variance in the spamming patterns. Further, we calculate the proximity between different spammers and classify them into various groups. Each group represents similar proximity. Spammers in the same group inherit similar patterns of spamming a domain. For classification into Botnet groups, we use clustering algorithms such as Hierarchical and K-means.We identify Botnet spammers into a particular group with a precision of 90%.

10abehavior pattern analysis10aBotnets10aClassification algorithms10aclustering algorithm10aClustering algorithms10aCorrelation10aElectronic mail10afeature set10aFiltering10ainformation filtering10ainvasive software10amaximum variance10apattern classification10apattern clustering10aPCA10aprincipal component analysis10aspam filtering10aTime frequency analysis10aunsolicited e-mail10aunwanted traffic control1 aHusna, Husain1 aPhithakkitnukoon, Santi1 aPalla, Srikanth1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/20001653nas a2200193 4500008004100000020002200041245004800063210004800111260002800159300001400187520108700201100002801288700001801316700001501334700001401349700002201363700002301385856005101408 2008 eng d a978-0-387-77672-900aBehavioral Entropy of a Cellular Phone User0 aBehavioral Entropy of a Cellular Phone User aBoston, MAbSpringer US a160–1673 a

The increase of advanced service offered by cellular networks draws lots of interest from researchers to study the networks and phone user behavior. With the evolution of Voice over IP, cellular phone usage is expected to increase exponentially. In this paper, we analyze the behavior of cellular phone users and identify behavior signatures based on their calling patterns. We quantify and infer the relationship of a person’s randomness levels using information entropy based on the location of the user, time of the call, inter-connected time, and duration of the call. We use real-life call logs of 94 mobile phone users collected at MIT by the Reality Mining Project group for a period of nine months. We are able to capture the user’s calling behavior on various parameters and interesting relationship between randomness levels in individual’s life and calling pattern using correlation coeffi- cients and factor analysis. This study extends our understanding of cellular phone user behavior and characterizes cellular phone users in forms of randomness level.

1 aPhithakkitnukoon, Santi1 aHusna, Husain1 aDantu, Ram1 aLiu, Huan1 aSalerno, John, J.1 aYoung, Michael, J. uhttp://dx.doi.org/10.1007/978-0-387-77672-9_1801936nas a2200349 4500008004100000245001700041210001700058260000800075520105100083653001201134653001701146653002701163653002601190653002101216653002101237653001401258653001101272653002301283653001601306653002501322653001901347653000901366653002701375653003301402653001701435653002801452653001801480653001701498100001901515700001501534856003701549 2008 eng d00aCall Algebra0 aCall Algebra cJan3 a

In every day life, people communicate through a voice(e.g., VoIP) network with different social groups that range from known people such as family members, friends, and distant relatives to unknown people such as spammers, telemarketers, and phishers. We believe that there exists a human/social dynamics between individuals by the way calls are generated, handled and received. In this paper we present how this dynamics can be used for detecting and filtering unwanted calls. In this paper, we first enumerate the communication patterns between the called party (callee) and the calling parties (callers). Next, we discuss operations on caller-callee matrices constructed based on their communication patterns, and derive call-constructs that can be used for determining the legitimacy of the calls and the callers. Finally, we discuss how these communication patterns and operations can be grouped for solutions to few of the existing IP telephony problems. These solutions can complement the existing no-call-lists in voice networks.

10aAlgebra10acall algebra10acaller-callee matrices10acommunication pattern10aComputer science10aContext modeling10aFiltering10aHumans10aInternet telephony10aIP networks10aIP telephony problem10amatrix algebra10aMood10aPeer to peer computing10asocial aspects of automation10asocial group10aSocial network services10avoice-over-IP10aVoIP network1 aKolan, Prakash1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/25101962nas a2200181 4500008004100000245003100041210003100072490000600103520151100109653002501620653002101645653001301666653000901679100001501688700002001703700002001723856003701743 2008 eng d00aClassification of phishers0 aClassification of phishers0 v53 a

Phishing attackers masquerade as genuine senders and try to steal consumers' personal identity data and financial account credentials. In spite of aggressive efforts, technology companies have had limited success in restricting phishing attacks. Unfortunately the nature of phishing attacks changed over time from passive, such as password guessing and eavesdropping to active attacks, such as employing Trojans to intercept traffic and adopting social engineering techniques. No matter how many authentication techniques we develop, phishers always adapt. However, phishers cannot become part of the recipient's social network without consent. Though they can forge certain fields in an email header, phishers do not have access to the complete header. In this paper, we describe techniques for detecting phishers based on their traffic paths, traffic patterns, and on the receivers' social network. Considering such issues, we based our solution on the trustworthiness of the relays participating in routing the emails. We examine the email's header rather than the content. We designed our classifier to perform the following analyses in four steps: i) DNS-header analysis, ii) Social network analysis, iii) Wantedness analysis, and iv) Proactive classification. We classify phishers into: i) Serial phishers, ii) Recent phishers, iii) Prospective phishers, and iv) Suspects. Finally, our classifier appends an alert level or label to the email's "subject" before adding the email to the inbox.

10aapplication security10anetwork security10aphishing10aspam1 aDantu, Ram1 aPalla, Srikanth1 aCangussu, João uhttps://nsl.cse.unt.edu/node/23501188nas a2200169 4500008004100000020002200041245006900063210006800132260004000200520061900240653002000859653002800879653001700907100002800924700001500952856005100967 2008 eng d a978-3-540-88874-100aCPL: Enhancing Mobile Phone Functionality by Call Predicted List0 aCPL Enhancing Mobile Phone Functionality by Call Predicted List aBerlin, HeidelbergbSpringer-Verlag3 a

In this paper, we present a concept of a new advanced feature for a mobile phone that provides its user functionality for predicting future calls. The feature is envisaged as a Call Predicted List (CPL) which makes use of the user’s call history to build a probabilistic model of calling behavior based on the caller’s calling patterns and reciprocity. The calling behavior model is then used to generate a list of numbers/contacts that are the most likely to be callers in the next hour. The performance of the CPL is evaluated with the real-life call logs and it shows promising results in accuracy.

10aCall prediction10aContext-aware computing10amobile phone1 aPhithakkitnukoon, Santi1 aDantu, Ram uhttp://dx.doi.org/10.1007/978-3-540-88875-8_8001226nas a2200169 4500008004100000020002200041245005700063210005700120260005900177520068100236100001700917700001500934700002100949700001600970700001900986856005101005 2008 eng d a978-3-540-88875-800aDiscovery of Social Groups Using Call Detail Records0 aDiscovery of Social Groups Using Call Detail Records aMonterrey, MexicobSpringer Berlin Heidelbergc11/20083 a

In this paper we propose the affinity model for classifying social groups based on mobile phone call detail records. We use affinity to measure the similarity between probability distributions. Since phone calls are stochastic process, it makes more sense to use probability affinity to classify the social groups. This work is useful for enhancing homeland security, detecting unwanted calls (e.g., spam) and product marketing. For validation of our results, we used actual call logs of 100 users collected at MIT by the Reality Mining Project group for a period of 8 months. The experimental results show that our model achieves good performance with high accuracy.

1 aZhang, Huiqi1 aDantu, Ram1 aMeersman, Robert1 aTari, Zahir1 aHerrero, Pilar uhttp://dx.doi.org/10.1007/978-3-540-88875-8_7202502nas a2200397 4500008004100000245006500041210006100106300001400167490000700181520139100188653001001579653002301589653002201612653002201634653002201656653001501678653002401693653002101717653001701738653002001755653001601775653002501791653002101816653002101837653002101858653002101879653002401900653001901924653002701943653002601970100001701996700002002013700001902033700001502052856003702067 2008 eng d00aEstimation of Defects Based on Defect Decay Model: ED^\{3\}M0 aEstimation of Defects Based on Defect Decay Model ED 3 M a336 - 3560 v343 a

An accurate prediction of the number of defects in a software product during system testing contributes not only to the management of the system testing process but also to the estimation of the product's required maintenance. Here, a new approach called ED3M is presented that computes an estimate of the total number of defects in an ongoing testing process. ED3M is based on estimation theory. Unlike many existing approaches the technique presented here does not depend on historical data from previous projects or any assumptions about the requirements and/or testers' productivity. It is a completely automated approach that relies only on the data collected during an ongoing testing process. This is a key advantage of the ED3M approach, as it makes it widely applicable in different testing environments. Here, the ED3M approach has been evaluated using five data sets from large industrial projects and two data sets from the literature. In addition, a performance analysis has been conducted using simulated data sets to explore its behavior using different models for the input data. The results are very promising; they indicate the ED3M approach provides accurate estimates with as fast or better convergence time in comparison to well-known alternative techniques, while only using defect data as the input.

10aCosts10adefect decay model10adefect estimation10aDefect prediction10aestimation theory10aInspection10aMetrics/Measurement10aPhase estimation10aProductivity10aprogram testing10aProgramming10aSoftware maintenance10asoftware metrics10asoftware product10aSoftware systems10aSoftware testing10aStatistical methods10aSystem testing10asystem testing process10aTesting and Debugging1 aHaider, Syed1 aCangussu, João1 aCooper, Kendra1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/21402939nas a2200457 4500008004100000245009700041210006900138260001000207520152900217653001301746653001801759653002301777653002301800653002301823653002401846653000901870653002301879653002901902653003001931653002801961653003201989653005202021653002002073653002902093653001702122653001802139653003602157653003202193653001202225653000702237653002002244653001802264653002802282653002902310653001802339653003002357100001502387700002502402700001702427856003702444 2008 eng d00aExperiences in building a multi-university testbed for research in multimedia communications0 aExperiences in building a multiuniversity testbed for research i cApril3 a

The next generation Internet needs to support multimedia services such as voice/video over IP (VoIP) and IP-based television (IPTV) and media distribution. The goal of the project is to develop a testbed for understanding and analysis of vulnerabilities of IP-based multimedia networks. This is a collaborative project between University of North Texas, Columbia University, Purdue University, and University of California at Davis. This project was awarded in 2006 and in one year, we have developed a multi-university testbed with variety of PBX solutions including Asterisk, a multitude of voice and video IP phones, and multiple universities were connected through a secure VPN and Internet!. As with any endeavor, experiences and we have many unique issues, which sometimes cause setbacks. We have dealt with issues concerning interoperability between phones and servers, network address translation (NAT) connectivity issues, and many other collaboration issues concerning people and technology. An interworking of students from multiple universities, faculty, system administrators and support personnel has brought the testbed resources together for a working environment. In this paper we described our progress and experiences in more detail and how to fulfill our mission statement while supporting the various collaborative efforts involved with this project. In addition, we described the current research activities based on the testbed. Finally we described the next steps in the testbed development.

10aAsterisk10aCollaboration10aCollaborative work10adigital television10aInternet telephony10aIP-based television10aIPTV10amedia distribution10aMultimedia communication10aMultimedia communications10amultiuniversity testbed10aNetwork address translation10anetwork address translation connectivity issues10aNetwork servers10anext generation Internet10aopen systems10aPBX solutions10aphones-servers interoperability10aprivate telephone exchanges10aTesting10aTV10avideo IP phones10avideo over IP10avirtual private network10avirtual private networks10avoice over IP10aWeb and internet services1 aDantu, Ram1 aSchulzrinne, Henning1 aSroufe, Paul uhttps://nsl.cse.unt.edu/node/24801487nas a2200229 4500008004100000020002200041245004500063210004500108260005100153300001400204520079800218653001801016653002601034653001901060100002801079700002801107700001501135700002101150700001601171700001901187856005101206 2008 eng d a978-3-540-88875-800aGroup Recommendation System for Facebook0 aGroup Recommendation System for Facebook aBerlin, HeidelbergbSpringer Berlin Heidelberg a211–2193 a

Online social networking has become a part of our everyday lives, and one of the popular online social network (SN) sites on the Internet is Facebook, where users communicate with their friends, join to groups, create groups, play games, and make friends around the world. Also, the vast number of groups are created for different causes and beliefs. However, overwhelming number of groups in one category causes difficulties for users to select a right group to join. To solve this problem, we introduce group recommendation system (GRS) using combination of hierarchical clustering technique and decision tree. We believe that Facebook SN groups can be identified based on their members’ profiles. Number of experiment results showed that GRS can make 73% accurate recommendation.

10adecision tree10arecommendation system10aSocial network1 aBaatarjav, Enkh-Amgalan1 aPhithakkitnukoon, Santi1 aDantu, Ram1 aMeersman, Robert1 aTari, Zahir1 aHerrero, Pilar uhttp://dx.doi.org/10.1007/978-3-540-88875-8_4103364nas a2200421 4500008004100000245016000041210006900201300001400270490000700284520195900291653003402250653001902284653002902303653002202332653002902354653002702383653003402410653002902444653002202473653002302495653001702518653002502535653002702560653004502587653002002632653004502652653001702697653002002714653002502734653003002759653001602789653002002805653001502825653002402840100002602864700001502890856003702905 2008 eng d00aAn Impatient Evolutionary Algorithm With Probabilistic Tabu Search for Unified Solution of Some NP-Hard Problems in Graph and Set Theory via Clique Finding0 aImpatient Evolutionary Algorithm With Probabilistic Tabu Search  a645 - 6660 v383 a

Many graph- and set-theoretic problems, because of their tremendous application potential and theoretical appeal, have been well investigated by the researchers in complexity theory and were found to be NP-hard. Since the combinatorial complexity of these problems does not permit exhaustive searches for optimal solutions, only near-optimal solutions can be explored using either various problem-specific heuristic strategies or metaheuristic global-optimization methods, such as simulated annealing, genetic algorithms, etc. In this paper, we propose a unified evolutionary algorithm (EA) to the problems of maximum clique finding, maximum independent set, minimum vertex cover, subgraph and double subgraph isomorphism, set packing, set partitioning, and set cover. In the proposed approach, we first map these problems onto the maximum clique-finding problem (MCP), which is later solved using an evolutionary strategy. The proposed impatient EA with probabilistic tabu search (IEA-PTS) for the MCP integrates the best features of earlier successful approaches with a number of new heuristics that we developed to yield a performance that advances the state of the art in EAs for the exploration of the maximum cliques in a graph. Results of experimentation with the 37 DIMACS benchmark graphs and comparative analyses with six state-of-the-art algorithms, including two from the smaller EA community and four from the larger metaheuristics community, indicate that the IEA-PTS outperforms the EAs with respect to a Pareto-lexicographic ranking criterion and offers competitive performance on some graph instances when individually compared to the other heuristic algorithms. It has also successfully set a new benchmark on one graph instance. On another benchmark suite called Benchmarks with Hidden Optimal Solutions, IEA-PTS ranks second, after a very recent algorithm called COVER, among its peers that have experimented with this suite.

10aAlgorithm design and analysis10aClique finding10acombinatorial complexity10aComplexity theory10acomputational complexity10aevolutionary algorithm10aevolutionary algorithms (EAs)10aevolutionary computation10agenetic algorithm10aGenetic algorithms10agraph theory10aHeuristic algorithms10amaximum clique finding10ametaheuristic global optimization method10aNP-hard problem10aNP-hard problems in set and graph theory10aoptimisation10aPareto analysis10aPerformance analysis10aprobabilistic tabu search10aprobability10asearch problems10aset theory10asimulated annealing1 aGuturu, Parthasarathy1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/20701290nas a2200181 4500008004100000020002200041245004400063210004400107260005900151300001400210520073400224100002800958700001500986700002101001700001601022700001901038856005101057 2008 eng d a978-3-540-88875-800aInferring Social Groups Using Call Logs0 aInferring Social Groups Using Call Logs aMonterrey, MexicobSpringer Berlin Heidelbergc11/2008 a200–2103 a

Recent increase in population of mobile phone users makes it a valuable source of information for social network analysis. For a given call log, how much can we tell about the person’s social group? Unnoticeably, phone user’s calling personality and habit has been concealed in the call logs from which we believe that it can be extracted to infer its user’s social group information. In this paper, we present an end-to-end system for inferring social networks based on “only” call logs using kernel-based naïve Bayesian learning. We also introduce normalized mutual information for feature selection process. Our model is evaluated with real-life call logs where it performs at high accuracy rate of 81.82%.

1 aPhithakkitnukoon, Santi1 aDantu, Ram1 aMeersman, Robert1 aTari, Zahir1 aHerrero, Pilar uhttp://dx.doi.org/10.1007/978-3-540-88875-8_4001140nas a2200205 4500008004100000245008900041210006900130260003800199520052200237653001000759653000900769653000800778653001200786653001300798100001500811700002100826700001700847700001900864856005100883 2008 eng d00aMethod and system for providing supplementary services for a wireless access network0 aMethod and system for providing supplementary services for a wir aUSbCisco Technology Incc10/20083 a

A method and system for providing supplementary services for a wireless access network includes downloading supplementary service triggers from a call agent to a mobility control function (MCF) for a wireless access network. Wireless-specific signaling of the wireless access network is communicated to the MCF. The MCF detects events associated with a trigger based on the wireless-specific signaling. The call agent is informed of the events by the MCF through session initiating protocol (SIP) extensions.

10aagent10acall10amcf10anetwork10awireless1 aDantu, Ram1 aChiang, Shihlung1 aYin, Haochih1 aKachhla, Rasik uhttps://patents.google.com/patent/US7444151/en01053nas a2200217 4500008004100000022001600041245007300057210006900130260003800199520042400237653001000661653000900671653000800680653001200688653001200700100001500712700002100727700001700748700001900765856005100784 2008 eng d aUS7471674B200aMethod and system of control signaling for a wireless access network0 aMethod and system of control signaling for a wireless access net aUSbCisco Technology Incc12/20083 a

A method and system of control signaling for a wireless access network includes receiving from a wireless access network a signaling message for a mobile device. The signaling message is in a wireless-specific format. The signaling message is converted to a native format of a call agent to generate a call agent message. The call agent message comprises wireless-specific information of the signaling message.

10aagent10acall10amcf10amessage10anetwork1 aDantu, Ram1 aChiang, Shihlung1 aYin, Haochih1 aKachhla, Rasik uhttps://patents.google.com/patent/US7471674/en01661nas a2200241 4500008004100000022001400041245003500055210003500090300001500125490000600140520105900146653001301205653003001218653001301248653001301261653001301274653001401287653001701301100001901318700001501337700002001352856004701372 2008 eng d a1551-685700aNuisance Level of a Voice Call0 aNuisance Level of a Voice Call a6:1–6:220 v53 a

In our everyday life, we communicate with many people such as family, friends, neighbors, and colleagues. We communicate with them using different communication media such as email, telephone calls, and face-to-face interactions. While email is not real-time and face-to-face communications require geographic proximity, voice and video communications are preferred over other modes of communication. However, real-time voice/video calls may create nuisance to the receiver. In this article, we describe a mathematical model for computing nuisance level of incoming voice/video calls. We computed the closeness and nuisance level using the calling patterns between the caller and the callee. To validate the nuisance model, we collected cell phone call records of real-life people at our university and computed the nuisance value for all voice calls. We validated the nuisance levels using the feedback from those real-life people. Such a nuisance model is useful for predicting unwanted voice and video sessions in an IP communication network.

10abehavior10aMultimedia communications10anuisance10apresence10aSecurity10atolerance10aunwantedness1 aKolan, Prakash1 aDantu, Ram1 aCangussu, João uhttp://doi.acm.org/10.1145/1404880.140488601364nas a2200181 4500008004100000245003600041210003600077260005800113520083600171653001301007653001201020653002301032653001901055100002801074700001501102700002801117856003701145 2008 eng d00aPrivacy Management for Facebook0 aPrivacy Management for Facebook aHyderabad, IndiabSpringer Berlin Heidelbergc12/20083 a

As more people adopt the Internet as a medium of communication, the Internet has developed into a virtual world and this has resulted in many online social networks (SN). MySpace and Facebook, two leading online SN sites, have a combined user base of 170 million as of 2008. SN sites started to offer developers open platforms that provide users’ profile information to the developers. Unfortunately, the applications can also be used to invade privacy and to harvest the users’ profile information without their acknowledgement. To address this vulnerability, we propose a privacy-management system that protects the accessibility of users’ profile. The system uses probabilistic approach based on information revelation of users. Our experimental result shows that the system can achieve high accuracy rate of 75%.

10aFacebook10aPrivacy10aPrivacy management10aSocial network1 aBaatarjav, Enkh-Amgalan1 aDantu, Ram1 aPhithakkitnukoon, Santi uhttps://nsl.cse.unt.edu/node/12702016nas a2200373 4500008004100000245004800041210004800089260000800137520093600145653002201081653003001103653002101133653002201154653002401176653001701200653002001217653002101237653002001258653003401278653003101312653002401343653001701367653000901384653003101393653001401424653002501438653002701463653002601490100001801516700002801534700002801562700001501590856003701605 2008 eng d00aQuantifying presence using calling patterns0 aQuantifying presence using calling patterns cJan3 a

Presence technology is going to be an integral part of the next generation of communication technology. It can eliminate telephone tag between two parties (caller and callee), which will increase productivity of the parties and reduce unnecessary bandwidth usage of unwanted calls. In this paper, we propose a Willingness Estimator that computes willingness level of a callee for receiving calls from a specified caller. By knowing the willingness value of the callee the caller can decide on proceeding with the call or not. The proposed Willingness Estimator is tested with real mobile user data, and these results are highly accurate. We measure willingness based on calling patterns (arrival time, location, day) of a caller to a callee and this could serve as one of the future presence based services. The results can be used in telecommunication networks such as PSTN, Cellular networks, and Voice over IP networks.

10acellular networks10aCommunications technology10aComputer science10aComputer security10aIntrusion detection10aLaboratories10aMobile handsets10amobile user data10aNetwork servers10anext generation communication10aNext generation networking10apresence technology10aProductivity10aPSTN10atelecommunication networks10atelephony10auser calling pattern10avoice over IP networks10awillingness estimator1 aHusna, Husain1 aPhithakkitnukoon, Santi1 aBaatarjav, Enkh-Amgalan1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/23002176nas a2200337 4500008004100000245004400041210004400085260000800129520120000137653001801337653002901355653002101384653002801405653002101433653001201454653002601466653002901492653002301521653002001544653002701564653003901591653001701630653001001647653004101657653003001698653001401728653002701742100001701769700001501786856003701801 2008 eng d00aQuantifying the Presence of Phone Users0 aQuantifying the Presence of Phone Users cJan3 a

Presence-enabled telephony services can reduce telephone tag and improve customer satisfaction. In this paper we proposed the Bayesian inference model to calculate the willingness level of the callee to accept calls. Before making a call, the caller may use the willingness calculator to find out whether the callee is available. Based on this level the user can make a decision whether to make a call. For validation of our results, we used actual call logs of 100 users collected at MIT by the Reality Mining Project group for a period of 8 months. We used time of the day, day of the week, talk-time and location for calculating the willingness level Our results show a good agreement between computed willingness level and the number of missed/rejected calls. This service can be included as part of the presence server. When deployed, this service can increase productivity, avoid unwanted calls and reduce the call traffic congestion. This service is beneficial to both subscribers and phone service providers. However, in order to make this service a reality, we need to take into account other factors such social closeness, proximity, multiplexity and reputation of the caller.

10aBayes methods10aBayesian inference model10aBayesian methods10acall traffic congestion10aComputer science10aContext10acustomer satisfaction10aMultimedia communication10aMultimedia systems10aNetwork servers10aphone service provider10apresence-enabled telephony service10aProductivity10aRoads10atelecommunication congestion control10atelecommunication traffic10atelephony10awillingness calculator1 aZhang, Huiqi1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/22801454nas a2200157 4500008004100000245005400041210005300095260001000148300001000158490000600168520100500174100002001179700001501199700002001214856006201234 2008 eng d00aSpam Classification Based on E-Mail Path Analysis0 aSpam Classification Based on EMail Path Analysis cApril a46-690 v23 a

Email spam is the most effective form of online advertising. Unlike telephone marketing, email spamming does not require huge human or financial resources investment. Most existing spam filtering techniques concentrate on the emails’ content. However, most spammers obfuscate their emails’ content to circumvent content-based spam filters. An integrated solution for restricting spam emails is needed as content analyses alone might not provide a solution for filtering unsolicited emails. Here we present a new method for isolating unsolicited emails. Though spammers obfuscate their emails’ content, they do not have access to all the fields in the email header. Our classification method is based on the path an email traverses instead of content. Overall, our classifier produced fewer false positives when compared to current filters such as SpamAssassin. We achieved a precision of 98.65% which compares well with the precisions achieved by SPF, DNSRBL blacklists.

1 aPalla, Srikanth1 aDantu, Ram1 aCangussu, João uhttps://ideas.repec.org/a/igg/jisp00/v2y2008i2p46-69.html02004nas a2200301 4500008004100000245003600041210003600077260002700113520114300140653002201283653002501305653001801330653001301348653002601361653001701387653002001404653001301424653002301437653004101460653003001501653003001531653002001561653002301581100001801604700002801622700001501650856003701665 2008 eng d00aTraffic Shaping of Spam Botnets0 aTraffic Shaping of Spam Botnets aLas Vegas, NVc01/20083 a

Compromised computers, known as bots, are the major source of spamming. Detecting them can help greatly improve control of unwanted traffic. In this paper, we develop a traffic control mechanism to detect and delay the traffic of suspicious senders and bots. By delaying spammer's traffic, it has been reported that 90% of spam emails can be eliminated. In our proposed mechanism, we group spammers based on their behavior and transmission patterns. These patterns of spammers show high correlation between group members irrespective of geographic location, network ID, content, and kind of receivers. After identification of these botnet groups we applied traffic shaping techniques a pre-filtering analysis to avoid use of automated machines(bots) to spam a particular domain. Thus the source for majority of spam is blocked before reaching email servers. We also identify how randomly the botnets behave and how easy it is to capture a botnet behavior, based on Information theory. To our knowledge, there is no work reported on detecting and mitigating botnets based on their behavior and in particular transmission patterns.

10aautomated machine10acompromised computer10aE-mail server10aInternet10aprefiltering analysis10aspam botnets10aspammer traffic10aspamming10asuspicious senders10atelecommunication network management10atelecommunication traffic10atraffic control mechanism10atraffic shaping10aunsolicited e-mail1 aHusna, Husain1 aPhithakkitnukoon, Santi1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/24101234nas a2200217 4500008004100000022001400041245004100055210004000096300001400136490000700150520067600157653001100833653002200844653000900866653001300875653000900888100002800897700001500925700002800940856004800968 2008 eng d a1939-355500aVoIP Security: Attacks and Solutions0 aVoIP Security Attacks and Solutions a114–1230 v173 a

Voice over IP (VoIP) technology is being extensively and rapidly deployed. Flexibility and cost efficiency are the key factors luring enterprises to transition to VoIP. Some security problems may surface with the widespread deployment of VoIP. This article presents an overview of VoIP systems and its security issues. First, we briefly describe basic VoIP architecture and its fundamental differences compared to PSTN. Next, basic VoIP protocols used for signaling and media transport, as well as defense mechanisms are described. Finally, current and potential VoIP attacks along with the approaches that have been adopted to counter the attacks are discussed.

10aattack10adefense mechanism10aPSTN10aSecurity10aVoIP1 aPhithakkitnukoon, Santi1 aDantu, Ram1 aBaatarjav, Enkh-Amgalan uhttp://dx.doi.org/10.1080/1939355080230861801295nas a2200133 4500008004100000245005500041210005200096300001000148490000600158520090900164100001501073700002001088856005301108 2007 eng d00aAn Architecture for Automatic and Adaptive Defense0 aArchitecture for Automatic and Adaptive Defense a37-580 v33 a

Network attacks have become so fast that human mitigation cannot cope with security requirements. In addition, attackers have become smarter by creating attacks which mutate themselves to prevent detection. Therefore, defense mechanisms must be automated to keep up with attack speed and adapted to seek out mutations. An architecture to support this trend in defense mechanisms is proposed here. The architecture is based upon three conceptual pillars. First is the use of a multi-feedback loop control to slow down an attack. Second, machine learning concepts are employed to properly distinguish between normal and abnormal e-attack traffic. And, third, trust and reputation levels are determined through social networks. A case study on the application of the proposed architecture to a worm propagation attack provides the initial evidence of the e-attack and applicability of the approach.

1 aDantu, Ram1 aCangussu, João uhttp://dx.doi.org/10.1080/15536548.2007.1085581502969nas a2200397 4500008004100000245007400041210006900115260000800184520175100192653002101943653003801964653004602002653001302048653001602061653002102077653001902098653002002117653002202137653001402159653002602173653002402199653002302223653003902246653001402285653004602299653002502345653002802370653003002398653001402428653001402442653002202456100001902478700002202497700001502519856003702534 2007 eng d00aAutomatic Calibration Using Receiver Operating Characteristics Curves0 aAutomatic Calibration Using Receiver Operating Characteristics C cJan3 a

Application-level filters, such as e-mail and VoIP spam filters, that analyze dynamic behavior changes are replacing static signature-recognition filters. These application-level filters learn behavior and use that knowledge to filter unwanted requests. Because behavior of a service request's participating entities changes rapidly, filters must adapt quickly by using end user's preferences about receiving that service request message. Many adaptive filters learn from the participating entities' behavior; however, none configure themselves automatically to an end user's changing tolerance levels. Also, filter administrators cannot manually change the threshold for each service request in real time. Traditional adaptive filters fail when administrators must optimize multiple filter thresholds manually and often. Thus, to improve a filter's learning, we must automate its threshold-update process. We propose an automatic threshold-calibration mechanism using Receiver Operating Characteristics (ROC) curves that updates the threshold based on an end user's feedback. To demonstrate the mechanism's real-time applicability, we integrated it in a Voice over IP (VoIP) spam filter that analyzes incoming Spam over IP Telephony (SPIT) calls. Using this mechanism, we observed good improvement in the VoIP spam filter's accuracy. Further, computing and updating the optimum threshold in realtime does not impede the filter's temporal performance because we update thresholds after each call's completion. Because we reach an optimum threshold for any initial setting, this mechanism works efficiently when we cannot predict end-user behavior. Furthermore, automatic calibration proves efficient when using multiple threshold values.

10aadaptive filters10aapplication-level filter learning10aautomatic threshold-calibration mechanism10abehavior10acalibration10aComputer science10aComputer worms10aElectronic mail10aend user feedback10aFiltering10ainformation filtering10ainformation filters10aInternet telephony10alearning (artificial intelligence)10aProtocols10areceiver operating characteristics curves10asensitivity analysis10aservice request message10atelecommunication traffic10aThreshold10atolerance10aViruses (medical)1 aKolan, Prakash1 aVaithilingam, Ram1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/22902241nas a2200313 4500008004100000245008900041210006900130260003100199520128100230653002101511653001801532653001801550653002101568653001301589653002001602653002201622653002001644653002501664653004701689653002001736653001301756653002801769653002701797100001501824700001901839700001601858700001601874856003701890 2007 eng d00aClassification of Attributes and Behavior in Risk Management Using Bayesian Networks0 aClassification of Attributes and Behavior in Risk Management Usi aNew Brunswick, NJc05/20073 a

Security administration is an uphill task to implement in an enterprise network providing secured corporate services. With the slew of patches being released by network component vendors, system administrators require a barrage of tools for analyzing the risk due to vulnerabilities in those components. In addition, criticalities in patching some end hosts raises serious security issues about the network to which the end hosts are connected. In this context, it would be imperative to know the risk level of all critical resources keeping in view the everyday emerging new vulnerabilities. We hypothesize that sequence of network actions by attackers depends on their social and attack profile (behavioral resources such as skill level, time, and attitude). To estimate the types of attack behavior, we surveyed individuals for their ability and attack intent. Using the individuals' responses, we determined their behavioral resources and classified them as having opportunist, hacker, or explorer behavior. The profile behavioral resources can be used for determining risk by an attacker having that profile. Thus, suitable vulnerability analysis and risk management strategies can be formulated to efficiently curtail the risk from different types of attackers.

10aattack behaviour10aattack graphs10aattack intent10aBayesian network10abehavior10abelief networks10aexplorer behavior10ahacker behavior10aopportunist behavior10aprofile behavioral resource classification10arisk management10aSecurity10asecurity administration10avulnerability analysis1 aDantu, Ram1 aKolan, Prakash1 aAkl, Robert1 aLoper, Kall uhttps://nsl.cse.unt.edu/node/22200612nas a2200241 4500008004100000022001400041245003800055210003800093300001400131490000700145653001100152653001100163653000800174653003900182653000900221653001300230653001000243653001700253100001500270700002200285700001500307856004800322 2007 eng d a0920-548900aEAP Methods for Wireless Networks0 aEAP Methods for Wireless Networks a289–3010 v2910a802.1110a802.1610aEAP10aExtensible authentication protocol10aRFID10aSecurity10aWiMAX10aWireless LAN1 aDantu, Ram1 aClothier, Gabriel1 aAtri, Anuj uhttp://dx.doi.org/10.1016/j.csi.2006.04.00102674nas a2200349 4500008004100000245004900041210004900090300001400139490000600153520156800159653005601727653002201783653003401805653003401839653001201873653002201885653002101907653004201928653001501970653002901985653003702014653005002051653001902101653003302120653002402153653003102177653002102208100001502229700002002244700002302264856003702287 2007 eng d00aFast Worm Containment Using Feedback Control0 aFast Worm Containment Using Feedback Control a119 - 1360 v43 a

In a computer network, network security is accomplished using elements such as firewalls, hosts, servers, routers, intrusion detection systems, and honey pots. These network elements need to know the nature or anomaly of the worm a priori to detect the attack. Modern viruses such as Code Red, Sapphire, and Nimda spread quickly. Therefore, it is impractical if not impossible for human mediated responses to these fast-spreading viruses. Several epidemic studies show that automatic tracking of resource usage and control provides an effective method to contain the damage. In this paper, we propose a novel security architecture based on the control system theory. In particular, we describe a state-space feedback control model that detects and control the spread of these viruses or worms by measuring the velocity of the number of new connections an infected host makes. The mechanism's objective is to slow down a worm's spreading velocity by controlling (delaying) the number of new connections made by an infected host. A proportional and integral (PI) controller is used for a continuous control of the feedback loop. The approach proposed here has been verified in a laboratory setup, and we were able to contain the infection so that it affected less than 5 percent of the hosts. We have also implemented a protocol for exchanging control-specific information between the network elements. The results from the simulation and experimental setup combined with the sensitivity analysis demonstrate the applicability and accuracy of the approach.

10acommunication/networking and information technology10acomputer networks10aComputer systems organization10acontrol engineering computing10ageneral10ainvasive software10anetwork security10anetwork-level security and protection10aPI control10aprocess control systems.10aproportional-integral controller10aspecial-purpose and application-based systems10astate feedback10astate-space feedback control10astate-space methods10atelecommunication security10aworm containment1 aDantu, Ram1 aCangussu, João1 aPatwardhan, Sudeep uhttps://nsl.cse.unt.edu/node/20201749nas a2200373 4500008004100000245005700041210005600098260000800154520063400162653003000796653002700826653002200853653002100875653001900896653002600915653001200941653002400953653002300977653002101000653001401021653002101035653002101056653001901077653003201096653003901128653003101167653003201198653002901230653002801259100001601287700002001303700001501323856003701338 2007 eng d00aGoliath: A Configurable Approach for Network Testing0 aGoliath A Configurable Approach for Network Testing cMay3 a

When testing a network environment and/or application many aspects need to be taken into consideration. For example, different software needs to be deployed at different nodes and different topologies may also need to be tested. The manual execution of these tasks are very time consuming and a configurable environment to facilitate these tasks and consequently improve testing performance is desired. In this paper a virtual network environment that can be easily reconfigured is presented to address this problem. Also presented is a case study with the results of deployment and containing a worm propagation attack.

10aautomated network testing10aComputational modeling10acomputer networks10aComputer science10aComputer worms10aDistributed computing10aGoliath10aIntrusion detection10anetwork topologies10aNetwork topology10aProtocols10asecurity of data10aSoftware testing10aSystem testing10atelecommunication computing10atelecommunication network topology10atelecommunication security10avirtual network environment10avirtual private networks10aworm propagation attack1 aFagen, Wade1 aCangussu, João1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/23101111nas a2200169 4500008004100000022001400041245003700055210003600092300001200128490000900140520066500149100001500814700002300829700001900852700001800871856005200889 2007 eng d a1353-485800aHIPAA: Securing Medical Networks0 aHIPAA Securing Medical Networks a13–160 v20073 a

The Health Information Portability and Accountability Act of 1996 (HIPAA) imposes strict regulations on healthcare institutions and commercial vendors to indemnify clinical data against unscrupulous users. Security vulnerabilities concerning hospital information systems not only negatively impact patient healthcare, but may also represent a potential federal violation. For a comprehensive understanding of the security of a radiology communication network, a detailed survey of the Picture Archiving and Communication Systems (PACS) was compiled. In this paper, we present survey results and a set of recommendations for implementing PACS security.

1 aDantu, Ram1 aOosterwijk, Herman1 aKolan, Prakash1 aHusna, Husain uhttp://dx.doi.org/10.1016/S1353-4858(07)70055-701294nas a2200253 4500008004100000022001600041245006900057210006900126260003800195520057500233653000900808653000900817653001200826653001200838653001300850100001500863700001700878700001800895700002200913700001900935700001700954700001800971856005100989 2007 eng d aUS7225238B100aMethod and system for providing services for wireless data calls0 aMethod and system for providing services for wireless data calls aUSbCisco Technology Incc05/20073 a

A method and system for providing services for wireless data calls includes monitoring a wireless data call for a predefined event associated with a service for the wireless data call. The service is initiated for the wireless data call in response to detecting the predefined event for the data call. The predefined event may comprise a uniform resource locator (URL) match or change, excess use of transmission or time resources, a location change of a mobile device for the wireless data call, a network event, or a combination of any or all suitable events.

10acall10adata10anetwork10aservice10awireless1 aDantu, Ram1 aPatel, Pulin1 aPatel, Pravir1 aGarbuz, Alexander1 aMiernik, Jerzy1 aPatel, Achal1 aHolur, Balaji uhttps://patents.google.com/patent/US7225238/en01676nas a2200289 4500008004100000245005900041210005800100260002900158520082200187653001701009653001301026653001601039653001101055653001101066653001901077653001901096653002301115653003301138653003001171653001901201653003901220653003101259653001601290100002801306700001501334856003701349 2007 eng d00aPredicting Calls: New Service for an Intelligent Phone0 aPredicting Calls New Service for an Intelligent Phone a San José, USAc11/20073 a

Predicting future calls can be the next advanced feature of the intelligent phone as the phone service providers are looking to offer new services to their customers. Call prediction can be useful to many applications such as planning daily schedule and attending unwanted communications (e.g. voice spam). Predicting calls is a very challenging task. We believe that this is a new area of research. In this paper, we propose a Call Predictor (CP) that computes the probability of receiving calls and makes call prediction based on caller’s behavior and reciprocity. The proposed call predictor is tested with the actual call logs. The experimental results show that the call predictor performs reasonably well with false positive rate of 2.4416%, false negative rate of 2.9191%, and error rate of 5.3606%.

10aArrival time10abehavior10acall matrix10aCallee10aCaller10aCommunications10aIncoming calls10aInter-arrival time10aInter-arrival/departure time10aKernel density estimation10aOutgoing calls10aProbability density function (pdf)10aReceiving call probability10aReciprocity1 aPhithakkitnukoon, Santi1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/16802897nas a2200205 4500008004100000022001400041245005100055210005000106490000600156520232400162653001302486653001502499653003802514653003402552653001402586653001002600100001902610700001502629856004702644 2007 eng d a1556-466500aSocio-technical Defense Against Voice Spamming0 aSociotechnical Defense Against Voice Spamming0 v23 a

Voice over IP (VoIP) is a key enabling technology for migration of circuit-switched PSTN (Public Switched Telephone Network) architectures to packet-based networks. One problem of the present VoIP networks is filtering spam calls referred to as SPIT (Spam over Internet Telephony). Unlike spam in e-mail systems, VoIP spam calls have to be identified in real time. Many of the techniques devised for e-mail spam detection rely upon content analysis, and in the case of VoIP, it is too late to analyze the content (voice) as the user would have already attended the call. Therefore, the real challenge is to block a spam call before the telephone rings. In addition, we believe it is imperative that spam filters integrate human behavioral aspects to gauge the legitimacy of voice calls. We know that, when it comes to receiving or rejecting a voice call, people use the social meaning of trust, reputation, friendship of the calling party and their own mood. In this article, we describe a multi-stage, adaptive spam filter based on presence (location, mood, time), trust, and reputation to detect spam in voice calls. In particular, we describe a closed-loop feedback control between different stages to decide whether an incoming call is spam. We further propose formalism for voice-specific trust and reputation analysis. We base this formal model on a human intuitive behavior for detecting spam based on the called party’s direct and indirect relationships with the calling party. No VoIP corpus is available for testing the detection mechanism. Therefore, for verifying the detection accuracy, we used a laboratory setup of several soft-phones, real IP phones and a commercial-grade proxy server that receives and processes incoming calls. We experimentally validated the proposed filtering mechanisms by simulating spam calls and measured the filter’s accuracy by applying the trust and reputation formalism. We observed that, while the filter blocks a second spam call from a spammer calling from the same end IP host and domain, the filter needs only a maximum of three calls—even in the case when spammer moves to a new host and domain. Finally, we present a detailed sensitivity analysis for examining the influence of parameters such as spam volume and network size on the filter’s accuracy

10abehavior10areputation10aSIP (Session Initiation Protocol)10aSPIT (Spam over IP Telephony)10atolerance10aTrust1 aKolan, Prakash1 aDantu, Ram uhttp://doi.acm.org/10.1145/1216895.121689701882nas a2200205 4500008004100000022001600041245012000057210006900177260002800246520125000274653001001524653001201534653000901546653001001555653000901565100001501574700001601589700002001605856005101625 2007 eng d aUS7167443B100aSystem and method for packet level restoration of IP traffic using overhead signaling in a fiber optic ring network0 aSystem and method for packet level restoration of IP traffic usi aUSbAlcatel SAc01/20073 a

An apparatus and a method for forwarding data packets through a fiber optic ring network includes forwarding data packets on a packet by packet basis. A node on the fiber optic ring network decides on a packet by packet basis whether to transmit on the working or protection path. Because this decision is being made on a packet level, reservation of throughput resources no longer is made at a one to one ratio. Rather, protection path resources are reserved at a ratio significantly less than one to one. In one embodiment, no resources are reserved for path restoration or protection path routing. Rather, quality of service provisioning is used to resolve interference situations wherein instantaneous demand exceeds capacity. A node evaluates ring conditions in relation to the demand of traffic resources and the relative quality of service ratings to determine whether and how to forward a packet. Additionally, a node decides whether to use the working or protection path by considering the final destination on the fiber optic ring network, any identified ring conditions and, in some embodiments, quality of service. The ring conditions to which the inventive nodes respond include OSI layer 1, layer 2 and layer 3 conditions.

10afiber10anetwork10anode10aoptic10aring1 aDantu, Ram1 aEster, Gary1 aO'Connell, Pete uhttps://patents.google.com/patent/US7167443/en00395nas a2200097 4500008003900000245009300039210006900132260004400201100001500245856003700260 2007 d00aA Testbed for Research and Development for Securing IP Multimedia Communication Services0 aTestbed for Research and Development for Securing IP Multimedia  aBoston, MAbNSF CRI PI Meetingc06/20071 aDantu, Ram uhttps://nsl.cse.unt.edu/node/18003010nas a2200361 4500008004100000245003500041210003500076260000800111520199500119653002102114653003102135653001902166653001702185653002302202653003102225653002902256653001202285653003002297653002602327653002402353653002502377653001602402653002902418653001902447653001102466653002402477653002302501653003202524653002002556100002002576700001502596856003702611 2007 eng d00aUnwanted SMTP Paths and Relays0 aUnwanted SMTP Paths and Relays cJan3 a

Based on the social interactions of an email user, incoming email traffic can be divided into different categories such as, telemarketing, Opt-in family members and friends. Due to a lack of knowledge in the different categories, most of the existing spam filters are prone to high false positives and false negatives. Moreover, a majority of the spammers obfuscate their email content inorder to circumvent the content-based spam filters. However, they do not have access to all the fields in the email header. Our classification method is based on the path traversed by email (instead of content analysis) since we believe that spammers cannot forge all the fields in the email header. We based our classification on three kinds of analyses on the header: i) EndToEnd path analysis, which tries to establish the legitimacy of the path taken by an email and classifies them as either spam or non-spam; ii) Relay analysis, which verifies the trustworthiness of the relays participating in the relaying of emails; iii) Emails wantedness analysis, which measure the recipients wantedness of the senders emails. We use the IMAP message status flags such as, message has been read, deleted, answered, flagged, and draft as an implicit feed back from the user in Emails wantedness analysis. Finally we classify the incoming emails as i) socially close (such as, legitimate emails from family, and friends), ii) socially distinct emails from strangers, iii) spam emails (for example, emails from telemarketers, and spammers) and iv) opt-in emails. Based on the relation between spamminess of the path taken by spam emails and the unwantedness values of the spammers, we classify spammers as i) prospective spammers, ii) suspects, iii) recent spammers and iv) serial spammers. Overall, our method resulted in far less false positives compared to current filters like SpamAssassin. We achieved a precision of 98.65% which is better than the precisions achieved by SPF and DNSBL blacklists.

10aComputer science10acontent-based spam filters10aCounterfeiting10aCredit cards10aemail spam filters10aemails wantedness analysis10aend-to-end path analysis10aFilters10aIMAP message status flags10ainformation filtering10ainformation filters10aInformation security10aLegislation10aMultimedia communication10arelay analysis10aRelays10aSMTP paths analysis10aunsolicited e-mail10aUnsolicited electronic mail10aWeb page design1 aPalla, Srikanth1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/24700334nas a2200097 4500008003900000245003300039210003300072260007900105100001500184856003700199 2006 d00aCISE and Global Implications0 aCISE and Global Implications aSnowbird, UtahbNSF Workshop on Computing Research Infrastructurec06/20061 aDantu, Ram uhttps://nsl.cse.unt.edu/node/19400277nas a2200097 4500008004100000245003300041210003300074100002000107700001500127856003700142 2006 eng d00aDetecting phishing in emails0 aDetecting phishing in emails1 aPalla, Srikanth1 aDantu, Ram uhttps://nsl.cse.unt.edu/node/16701365nas a2200169 4500008004100000022001400041245005900055210005900114300001200173490000700185520088100192100002501073700001801098700001501116700001601131856004801147 2006 eng d a1572-945100aDynamic resource management in QoS controlled networks0 aDynamic resource management in QoS controlled networks a11–300 v323 a

This paper addresses the problem of resource fragmentation (RF) in QoS controllednetworks. Resources are said to be fragmented when they are available in non-contiguousblocks and hence cannot be utilized by incoming calls with high resource demands. This paper shows the effect of resource fragmentation on QoS controlled networks and presents the Dynamic Resource Redistribution (DRR) algorithm to counteract RF. The DRR algorithm reduces the effects of RF by attempting to redistribute resources in different paths to make resources to incoming calls. A variety of simulation experiments were conducted to study the performance of the DRR algorithm on different network topologies with varying traffic characteristics. The DRR algorithm, when used, increased the number of calls accommodated in the network as well as the overall resource allocation in the network.

1 aPrasanna, Venkatesan1 aMikler, Armin1 aDantu, Ram1 aAbbas, Kaja uhttp://dx.doi.org/10.1007/s11235-006-8200-400286nas a2200097 4500008003900000245001900039210001900058260005900077100001500136856003700151 2006 d00aFuture Threats0 aFuture Threats bNSF Workshop on Future Topics for Cyber Trustc09/20061 aDantu, Ram uhttps://nsl.cse.unt.edu/node/19501094nas a2200217 4500008004100000022001600041245006800057210006800125260003800193520046500231653001500696653001100711653001000722653000900732653001300741100001700754700001700771700002200788700001500810856005100825 2006 eng d aUS7031266B100aMethod and system for configuring wireless routers and networks0 aMethod and system for configuring wireless routers and networks aUSbCisco Technology Incc04/20063 a

A method and system for configuring a wireless router and a wireless communications network includes establishing connectivity between a wireless router and at least one wireline router. Connectivity between the wireless router and a plurality of neighboring wireless routers is established through the wireline router. The wireless router is configured based on information exchanged with the neighboring wireless routers through the wireline router.

10aparameters10arouter10astate10astep10awireless1 aPatel, Pulin1 aChoksi, Ojas1 aDavidson, Kenneth1 aDantu, Ram uhttps://patents.google.com/patent/US7031266/en00954nas a2200205 4500008004100000245007300041210006900114260003800183520035100221653001000572653001400582653000900596653001200605653001000617100001900627700001500646700001800661700001800679856005100697 2006 eng d00aQuality indicator and method for frame selection in wireless network0 aQuality indicator and method for frame selection in wireless net aUSbCisco Technology Incc07/20063 a

A method and system for indicating quality of a radio frame transmitted over a wireless link includes receiving a radio frame from the wireless link. A power indicator for the radio frame is determined based on a power control trend of the wireless link. A quality indicator for the radio frame is generated based on the power indicator.

10aframe10aindicator10alink10aquality10aradio1 aAlam, Mahbubul1 aDantu, Ram1 aHolur, Balaji1 aEyceoz, Tugay uhttps://patents.google.com/patent/US7079512/en00312nas a2200097 4500008004100000245002600041210002600067260006900093100001500162856003700177 2006 eng d00aSecuring IMS and VoIP0 aSecuring IMS and VoIP aBerlin, Germanyb3rd Workshop on Voice over IP Securityc06/20061 aDantu, Ram uhttps://nsl.cse.unt.edu/node/16500721nas a2200277 4500008004100000022001400041245002700055210002700082260000900109300000800118490000700126653001900133653002800152653002600180653002400206653002500230653002300255653002100278653001500299653001400314653002000328100001500348700001800363700002500381856003700406 2006 eng d a0890-804400aSecuring voice over IP0 aSecuring voice over IP cSept a4-50 v2010aAuthentication10aFingerprint recognition10ainformation filtering10ainformation filters10aInformation security10aInternet telephony10aMarkup languages10aProtection10aProtocols10aStandardization1 aDantu, Ram1 aGhosal, Dipak1 aSchulzrinne, Henning uhttps://nsl.cse.unt.edu/node/19101300nas a2200241 4500008004100000245007700041210006900118520058600187653002500773653002400798653002300822653001600845653000900861653002200870653001400892653001200906653002200918653002300940100001900963700001500982700002400997856003701021 2006 eng d00aSecuring VoIP and PSTN from integrated signaling network vulnerabilities0 aSecuring VoIP and PSTN from integrated signaling network vulnera3 a

The liberalization of public switched telephone network (PSTN) and growing acceptance of SIGTRAN protocol suite have introduced new and yet to be trusted signaling entities. Thus security threats emerging from one network not only affects itself but other network also. We show how this integrated signaling environment can become a security threat to emerging VoIP and PSTN networks. We propose a security solution as a fix. Our proposal goes beyond "Gateway Screening" and "SS7 Gatekeeper" proposed by Telcordia and Verizon respectively to defend vulnerable SS7 network.

10aInformation security10aInformation systems10aInternet telephony10aIP networks10aISDN10aNational security10aProtocols10aRouting10aSignal processing10aSwitching circuits1 aSengar, Hemant1 aDantu, Ram1 aWijesekera, Duminda uhttps://nsl.cse.unt.edu/node/21502611nas a2200469 4500008004100000022001400041245005600055210005500111260000800166300001000174490000700184520129100191653003401482653003001516653001801546653002301564653000901587653004001596653003601636653002301672653001901695653001601714653000901730653003501739653001401774653002101788653001201809653002101821653002101842653002701863653001201890653001601902653001301918653003301931653003201964653003001996100001902026700001502045700002402060700002002084856003702104 2006 eng d a0890-804400aSS7 over IP: signaling interworking vulnerabilities0 aSS7 over IP signaling interworking vulnerabilities cNov a32-410 v203 a

Public telephony - the preferred choice for two-way voice communication over a long time - has enjoyed remarkable popularity for providing acceptable voice quality with negligible connection delays, perhaps due to its circuit-switched heritage. Recently, IP telephony, a packet-based telephone service that runs as an application over the IP protocol, has been gaining popularity. To provide seamless interconnectivity between these two competing services, the Internet Engineering Task Force (IETF) has designed a signaling interface commonly referred to as SIGTRAN. This seamless intersignaling provided by SIGTRAN facilitates any subscriber in one network to reach any other subscriber in the other network, passing through any heterogeneous maze of networks consisting of either of these. Unfortunately, the same intersignaling potentially can be exploited from either side to disrupt the services provided on the other side. We show how this can be done and propose a solution based on access control, signal screening, and detecting anomalous signaling. We argue that to be effective, the latter two should consider syntactic correctness, semantic validity of the signal content, and the appropriateness of a particular signal in the context of earlier exchanged messages

10aanomalous signaling detection10acircuit-switched heritage10aDelay effects10aDesign engineering10aIETF10aIntegrated circuit interconnections10aInternet Engineering Task Force10aInternet telephony10aintersignaling10aIP protocol10aISDN10apacket-based telephone service10aProtocols10apublic telephony10aRouting10aSignal detection10asignal screening10asignaling interworking10aSIGTRAN10aSS7 over IP10aSwitches10atelecommunication signalling10atwo-way voice communication10aWeb and internet services1 aSengar, Hemant1 aDantu, Ram1 aWijesekera, Duminda1 aJajodia, Sushil uhttps://nsl.cse.unt.edu/node/21800625nas a2200193 4500008004100000022001600041245009500057210006900152260004100221653000700262653000900269653001200278653000900290653001400299100001500313700001800328700001900346856006600365 2006 eng d aUS7006433B100aSystem and method for transporting in/ain signaling over an internet protocol (IP) network0 aSystem and method for transporting inain signaling over an inter aUSbAlcatel USA Sourcing LPc02/200610aip10alink10anetwork10asctp10asignaling1 aDantu, Ram1 aDavis, Robert1 aGeorge, Thomas uhttps://patents.google.com/patent/US7006433B1/en?oq=US700643300429nas a2200097 4500008004100000245009000041210006900131260007900200100001500279856003700294 2006 eng d00aA Testbed for Research and Development For Securing Multimedia Communication Services0 aTestbed for Research and Development For Securing Multimedia Com aSnowbird, UtahbNSF Workshop on Computing Research Infrastructurec06/20061 aDantu, Ram uhttps://nsl.cse.unt.edu/node/19300406nas a2200097 4500008003900000245005300039210005300092260011100145100001500256856003700271 2006 d00aTop 3 challenges in VoIP Security and Management0 aTop 3 challenges in VoIP Security and Management aVancouver, BC, Canadab1st IEEE International Workshop on VoIP Security and Management (VoIPMaSE)c04/20061 aDantu, Ram uhttps://nsl.cse.unt.edu/node/19201815nas a2200253 4500008004100000022001600041245009100057210006900148260003800217520107200255653001201327653001101339653001201350653001201362653001301374100001501387700001701402700001701419700001701436700001801453700001901471700001801490856005301508 2006 eng d aUS7068624B100aWireless router and method for processing traffic in a wireless communications network0 aWireless router and method for processing traffic in a wireless  aUSbCisco Technology Incc06/20063 a

A wireless communications network includes a wireless-specific router topology layer that connects cellular sites to a wireline topology. The wireless-specific router topology provides a distributed architecture in which call processing including call setup, resource preservation, air bandwidth allocation, switching, soft handoff, and micromobility is performed at the cell level. The wireless routers are technology independent to support various cellular technologies. The wireless router may include a first interface operable to communicate wireless packets for a call with a remote device and a second interface operable to communicate wireline packets for the call with the wireline network. A traffic controller is coupled to the first and second interfaces and operable to convert traffic between the wireless and wireline packets and to route packets to a destination mobile or wireline device. A selection and distribution unit is operable to select and distribute traffic to support soft handoff for calls in the wireless communications network.

10anetwork10arouter10arouters10atraffic10awireless1 aDantu, Ram1 aPatel, Pulin1 aChoksi, Ojas1 aPatel, Achal1 aAli, Mohammad1 aMiernik, Jerzy1 aHolur, Balajl uhttps://patents.google.com/patent/US7068624B1/en00435nas a2200121 4500008004100000020003700041245006400078210006100142260003300203100001500236700002000251856004200271 2005 eng d a3-540-25999-6, 978-3-540-25999-200aAn Architecture for Network Security Using Feedback Control0 aArchitecture for Network Security Using Feedback Control aAtlanta, GAbSpringer-Verlag1 aDantu, Ram1 aCangussu, João uhttp://dx.doi.org/10.1007/11427995_8400347nas a2200097 4500008004100000245005500041210005300096260004800149100001500197856003700212 2005 eng d00aA Blueprint for Implementing Security in Radiology0 aBlueprint for Implementing Security in Radiology bAHRA Electronic Imaging Conferencec04/20051 aDantu, Ram uhttps://nsl.cse.unt.edu/node/16401769nas a2200121 4500008004100000245003600041210003600077260004200113520140400155100001501559700001901574856005401593 2005 eng d00aDetecting Spam in VoIP Networks0 aDetecting Spam in VoIP Networks aBerkeley, CA, USAbUSENIX Association3 a

Voice over IP (VoIP) is a key enabling technology for the migration of circuit-switched PSTN architectures to packetbased networks. The problem of spam in VoIP networks has to be solved in real time compared to e-mail systems. Many of the techniques devised for e-mail spam detection rely upon content analysis and in the case of VoIP it is too late to analyze the media after picking up the receiver. So we need to stop the spam calls before the telephone rings. From our observation, when it comes to receiving or rejecting a voice call people use social meaning of trust and reputation of the calling party. In this paper, we describe a multi-stage spam filter based on trust, and reputation for detecting the spam. In particular we used closed loop feedback between different stages in deciding if the incoming call is a spam or not. For verifying the concepts, we used a laboratory setup of several thousand soft-phones and a commercial grade proxy server. We verified our filtering mechanisms by simulating the spam calls and measured the accuracy of the filter. Results show that multistage feedback loop fares better than any single stage. Also, the larger the network size, the harder to detect a spam call. Further work includes understanding the behavior of different controlling parameters in trust and reputation calculations and deriving meaningful relationships between them.

1 aDantu, Ram1 aKolan, Prakash uhttp://dl.acm.org/citation.cfm?id=1251282.125128700416nas a2200097 4500008004100000245008200041210006900123260007400192100001500266856003700281 2005 eng d00aHospital Network Security: A Blueprint for Implementing Security in Radiology0 aHospital Network Security A Blueprint for Implementing Security  aPlano, Texas, USAbFirst Annual Internet Security Conferencec06/20051 aDantu, Ram uhttps://nsl.cse.unt.edu/node/18800995nas a2200181 4500008004100000022001600041245010600057210006900163260003800232520042200270653001200692653000900704653001000713653000900723653001300732100001500745856005300760 2005 eng d aUS6904286B100aMethod and system of integrated rate control for a traffic flow across wireline and wireless networks0 aMethod and system of integrated rate control for a traffic flow  aUSbCisco Technology Incc06/20053 a

A method and system of integrated rate control for a traffic flow extending across wireline and wireless networks includes determining a power indicator for a wireless link of a traffic flow between a source and a mobile device. Delivery of a feedback message generated by the mobile device is shaped based on the power indicator for the wireless link to control the source transmit rate of the traffic flow.

10acontrol10aflow10apower10arate10awireless1 aDantu, Ram uhttps://patents.google.com/patent/US6904286B1/en00344nas a2200097 4500008003900000245004200039210004100081260007200122100001500194856003700209 2005 d00aPanel: What do you mean security VoIP0 aPanel What do you mean security VoIP bIEEE ENTNET conference in conjunction with Supercom’2005c06/20051 aDantu, Ram uhttps://nsl.cse.unt.edu/node/18902129nas a2200133 4500008004100000020003700041245005900078210005900137260003300196520169000229100001501919700001901934856004201953 2005 eng d a3-540-25999-6, 978-3-540-25999-200aRisk Management Using Behavior Based Bayesian Networks0 aRisk Management Using Behavior Based Bayesian Networks aAtlanta, GAbSpringer-Verlag3 a

Security administration is an uphill task to implement in an enterprise network providing secured corporate services. With the slew of patches being released by Microsoft, HP and other vendors, system administrators require a barrage of tools for analyzing the risk due to these vulnerabilities. In addition to this, criticalities in patching some end hosts (eg., in hospitals) raises serious security issues about the network to which the end hosts are connected. In this context, it would be imperative to know the risk level of all critical resources (e.g., Oracle Server in HR department) keeping in view the everyday emerging new vulnerabilities. We hypothesize that sequence of network actions by an attacker depends on the social behavior (e.g., skill level, tenacity, financial ability). We extended this and formulated a mechanism to estimate the risk level of critical resources that may be compromised based on attacker behavior. This estimation is accomplished using behavior based attack graphs. These graphs represent all the possible attack paths to all the critical resources. Based on these graphs, we calculate the risk level of a critical resource using Bayesian methodology and periodically update the subjective beliefs about the occurrence of an attack. Such a calculated risk level would be a measure of the vulnerability of the resource and it forms an effective basis for a system administrator to perform suitable changes to network configuration. Thus suitable vulnerability analysis and risk management strategies can be formulated to efficiently curtail the risk from different types of attackers (script kiddies, hackers, criminals and insiders).

1 aDantu, Ram1 aKolan, Prakash uhttp://dx.doi.org/10.1007/11427995_1000321nas a2200097 4500008004100000245004500041210004500086260004000131100001500171856003700186 2005 eng d00aSecurity and Privacy issues in Radiology0 aSecurity and Privacy issues in Radiology bNSF Cyber Trust PI meetingc09/20051 aDantu, Ram uhttps://nsl.cse.unt.edu/node/19001927nas a2200145 4500008004100000020003700041245005600078210005600134260003300190520146500223100001501688700002001703700001601723856004201739 2005 eng d a3-540-25999-6, 978-3-540-25999-200aSensitivity Analysis of an Attack Containment Model0 aSensitivity Analysis of an Attack Containment Model aAtlanta, GAbSpringer-Verlag3 a

A feedback control model has been previously proposed to regulate the number of connections at different levels of a network. This regulation is applied in the presence of a worm attack resulting in a slow down of the spreading worm allowing time to human reaction to properly eliminate the worm in the infected hosts. The feedback model constitutes of two queues, one for safe connections and another for suspected connections. The behavior of the proposed model is based on three input parameters to the model. These parameters are: (i) the portion of new connection requests to be sent to the suspect queue, (ii) the number of requests to be transferred from the suspect to the safe queue, and (iii) the time out value of the requests waiting in the suspect queue. The more we understand the effects of these parameters on the model, the better we can calibrate the model. Based on this necessity, a sensitivity analysis of the model is presented here. The analysis allows for the computation of the effects of changing parameters in the output of the model. In addition, the use of a sensitivity matrix permits the computations of not only changes in one parameter but also combined changes of these parameters. From the sensitivity analysis we have verified our assumption that the changes in the input parameters have no effect on the overall system stability. However, there will be a short period of instability before reaching a stable state.

1 aDantu, Ram1 aCangussu, João1 aTuri, Janos uhttp://dx.doi.org/10.1007/11427995_1100477nas a2200133 4500008003900000245010400039210006900143100001600212700002000228700001500248700002400263700001900287856003700306 2005 d00aSignaling System 7 (SS7) Message Transfer Part 2 (MTP2) - User Peer-to-Peer Adaptation Layer (M2PA)0 aSignaling System 7 SS7 Message Transfer Part 2 MTP2 User PeertoP1 aGeorge, Tom1 aBidulock, Brian1 aDantu, Ram1 aSchwarzbauer, Hanns1 aMorneault, Ken uhttps://nsl.cse.unt.edu/node/18200364nas a2200097 4500008004100000245005300041210005200094260006800146100001500214856003700229 2005 eng d00aTechnology and Policy in securing Voice over IP0 aTechnology and Policy in securing Voice over IP aWashington, DCb2nd Workshop on Voice over IP Securityc06/20051 aDantu, Ram uhttps://nsl.cse.unt.edu/node/16200283nas a2200109 4500008004100000245002900041210002900070260001200099300001000111100001500121856003700136 2005 eng d00aTo Patch or Not to Patch0 aTo Patch or Not to Patch c04/2005 a48-491 aDantu, Ram uhttps://nsl.cse.unt.edu/node/16300360nas a2200109 4500008004100000245006100041210006100102260001200163100001500175700002300190856003700213 2005 eng d00aTop Ten Recommendations for PACS Security Implementation0 aTop Ten Recommendations for PACS Security Implementation c03/20051 aDantu, Ram1 aOosterwijk, Herman uhttps://nsl.cse.unt.edu/node/18301323nas a2200133 4500008004100000020001800041245004900059210004900108260004700157520089700204100001501101700002101116856005201137 2004 eng d a0-7695-2108-800aCollaborative Vision Using Networked Sensors0 aCollaborative Vision Using Networked Sensors aWashington, DC, USAbIEEE Computer Society3 a

Large numbers of sensors networked together form a powerful infrastructure for a wide variety of applications in health, military, home, manufacturing, and disaster areas. Networked video sensors over a geographical area can automatically detect the objects in that geographical area. However, real-time central processing of the large amount of data generated by the individual image sensors places significant demands on the bandwidth and the central processor. In this paper, we address this issue by introducing a novel concept of super-sensor that is based on selforganization and collaboration between several tens of sensors. As an example, we describe a histogram calculation that uses recursive doubling for global collaboration between sensors. We compare the performance of our networked super-sensor with conventional image processing algorithms run on a single processor

1 aDantu, Ram1 aJoglekar, Sachin uhttp://dl.acm.org/citation.cfm?id=977403.97844402203nas a2200373 4500008004100000245005900041210005900100260000800159520112600167653001401293653001501307653002601322653001601348653003301364653003201397653001501429653002401444653003201468653001001500653001901510653001601529653002701545653002801572653001801600653004201618653002801660653002401688653001201712100001501724700001601739700001901755700001801774856003701792 2004 eng d00aData centric modeling of environmental sensor networks0 aData centric modeling of environmental sensor networks cNov3 a

Meteorological and hydrological sensors deployed over several hundred kilometers of geographical area comprise an environmental sensor network. Large amounts of data need to be processed in minimal time and transmitted over the available low speed and low bandwidth links. This paper describes algorithms for optimal data collection and data fusion. An inductive model using exponential back-off policy is used to collect optimal amount of data. The data measurements for temperature, pH and specific conductance collected for a year from the sensors deployed at Lake Lewisville are used to test the inductive model. Energy savings of 90% are achieved even with 1% of degree of tolerance. The problem of data fusion is addressed by the introduction of a novel concept of a super-sensor, based on self-organization and collaboration among sensors. A histogram application is described that uses recursive doubling for global collaboration between sensors. The performance of the networked super-sensor in comparison to a centralized polling approach is analyzed for optimality on two different geographical areas.

10aBandwidth10abiosensors10adata centric modeling10adata fusion10aenvironmental sensor network10aexponential back-off policy10aHistograms10ahydrological sensor10aInternational collaboration10aLakes10ameteorological10aMeteorology10anetworked super-sensor10aoptimal data collection10asensor fusion10aSensor phenomena and characterization10aTemperature measurement10atemperature sensors10aTesting1 aDantu, Ram1 aAbbas, Kaja1 aO'Neill, Marty1 aMikler, Armin uhttps://nsl.cse.unt.edu/node/22500345nas a2200097 4500008004100000245004700041210004700088260006000135100001500195856003700210 2004 eng d00aDifferences between VoIP and Data Security0 aDifferences between VoIP and Data Security aAustin, Texas, USAbInternet2 workshop on VoIPc09/20041 aDantu, Ram uhttps://nsl.cse.unt.edu/node/16600426nas a2200133 4500008004100000020001800041245004000059210004000099260004700139100001500186700002000201700001900221856005200240 2004 eng d a0-7695-2108-800aDynamic Control of Worm Propagation0 aDynamic Control of Worm Propagation aWashington, DC, USAbIEEE Computer Society1 aDantu, Ram1 aCangussu, João1 aYelimeli, Arun uhttp://dl.acm.org/citation.cfm?id=977403.97841100449nas a2200145 4500008003900000022001400039245006500053210006300118260002400181100001200205700001500217700001900232700001500251856003700266 2004 d a2070-172100aForwarding and Control Element Separation (ForCES) Framework0 aForwarding and Control Element Separation ForCES Framework bRFC Editorc04/20041 aYang, L1 aDantu, Ram1 aAnderson, Todd1 aGopal, Ram uhttps://nsl.cse.unt.edu/node/21202256nas a2200145 4500008004100000020001800041245005500059210005500114260004700169520179200216100001502008700001602023700001902039856005202058 2004 eng d a0-7695-2108-800aRisk Management Using Behavior Based Attack Graphs0 aRisk Management Using Behavior Based Attack Graphs aWashington, DC, USAbIEEE Computer Society3 a

Security administration is an uphill task to implement inan enterprise network providing secured corporateservices. With the slew of patches being released byMicrosoft, HP and other vendors, system administratorsrequire a barrage of tools for analyzing the risk due tothese vulnerabilities. In addition to this, criticalities inpatching some end hosts (eg., in hospitals) raises serioussecurity issues about the network to which the end hostsare connected. In this context, it would be imperative toknow the risk level of all critical resources (e.g., OracleServer in HR department) keeping in view the everydayemerging new vulnerabilities. We hypothesize thatsequence of network actions by an attacker depends onthe social behavior (e.g., skill level, tenacity, financialability). By verifying our hypothesis on hacker emailcommunications, we extended this methodology andcalculated risk level for a small network. Towards thisgoal, we formulated a mechanism to estimate the risklevel of critical resources that may be compromisedbased on attacker behavior. This estimation isaccomplished using behavior based attack graphs. Thesegraphs represent all the possible attack paths to all thecritical resources. Based on these graphs, we calculatethe risk level of a critical resource using Bayesianmethodology and periodically update the subjectivebeliefs about the occurrence of an attack Such acalculated risk level would be a measure of thevulnerability of the resource and it forms an effectivebasis for a system administrator to perform suitablechanges to network configuration. Thus suitablevulnerability analysis and risk management strategiescan be formulated to efficiently curtail the risk fromdifferent types of attacker (script kiddies, hackers,criminals and insiders).

1 aDantu, Ram1 aLoper, Kall1 aKolan, Prakash uhttp://dl.acm.org/citation.cfm?id=977403.97838900353nas a2200109 4500008004100000245005200041210005200093260002300145100001500168700002300183856003700206 2004 eng d00aSurvey on Hospital Network Security and Privacy0 aSurvey on Hospital Network Security and Privacy bBarco Ltdc08/20041 aDantu, Ram1 aOosterwijk, Herman uhttps://nsl.cse.unt.edu/node/18700290nas a2200097 4500008004100000245002500041210002400066260005000090100001500140856003700155 2004 eng d00aVoIP: Are We Secured0 aVoIP Are We Secured aPlano, TX, USAbVoIP: Are We Securedc06/20041 aDantu, Ram uhttps://nsl.cse.unt.edu/node/18500301nas a2200097 4500008004100000245001800041210001800059260007400077100001500151856003700166 2004 eng d00aVoIP Security0 aVoIP Security aDallas, Texas, USAbAnnual DFW Secret Service Agents Meetingc07/20041 aDantu, Ram uhttps://nsl.cse.unt.edu/node/18600307nas a2200097 4500008004100000245001800041210001800059260008000077100001500157856003700172 2004 eng d00aVoIP Security0 aVoIP Security aDallas, Texas, USAb3rd Annual Dallas Wireless Security Conferencec05/20041 aDantu, Ram uhttps://nsl.cse.unt.edu/node/18400976nas a2200205 4500008003900000245006100039210006100100260002400161520038200185100001900567700001400586700001500600700001600615700001500631700001700646700002200663700002400685700002400709856003700733 2003 d00aRequirements for Separation of IP Control and Forwarding0 aRequirements for Separation of IP Control and Forwarding bRFC Editorc11/20033 a

This document introduces the Forwarding and Control Element Separation (ForCES) architecture and defines a set of associated terminology.  This document also defines a set of architectural, modeling, and protocol requirements to logically separate the control and data forwarding planes of an IP (IPv4, IPv6, etc.) networking device.

1 aAnderson, Todd1 aBowen, Ed1 aDantu, Ram1 aDoria, Avri1 aGopal, Ram1 aSalim, Jamal1 aKhosravi, Hormuzd1 aMinhazuddin, Muneyb1 aWasserman, Margaret uhttps://nsl.cse.unt.edu/node/17600719nas a2200241 4500008003900000245008100039210006900120100001900189700001700208700001500225700001700240700001900257700002000276700001500296700001900311700002000330700001900350700001800369700001900387700001700406700001400423856004000437 2002 d00aConstraint-Based Label Switched Path Setup using Label Distribution Protocol0 aConstraintBased Label Switched Path Setup using Label Distributi1 aAndersson, Loa1 aCallon, Ross1 aDantu, Ram1 aDoolan, Paul1 aFeldman, Nancy1 aFredette, Andre1 aGray, Eric1 aHeinanen, Juha1 aJamoussi, Bilel1 aKilty, Timothy1 aMalis, Andrew1 aGirish, Muckai1 aWorster, Tom1 aWu, Liwen uhttps://tools.ietf.org/html/rfc321200458nas a2200133 4500008003900000245008400039210006900123100001900192700001500211700002100226700002000247700001700267856004000284 2002 d00aSignaling System 7 (SS7) Message Transfer Part 2 (MTP2) - User Adaptation Layer0 aSignaling System 7 SS7 Message Transfer Part 2 MTP2 User Adaptat1 aMorneault, Ken1 aDantu, Ram1 aSidebottom, Greg1 aBidulock, Brian1 aHeitz, Jacob uhttps://tools.ietf.org/html/rfc333102011nas a2200133 4500008004100000022001900041245008000060210006900140260003700209520146800246100001501714700002001729856012801749 2001 eng d aEP1083696 (A2)00aSystem and method for packet level distributed routing in fiber optic rings0 aSystem and method for packet level distributed routing in fiber  bAlcatel USA Sourcing LPc03/20013 a

IP user traffic is transporting over a fiber optic ring network that includes a plurality of fiber optic ring network nodes. One (108) ring is for conducting the user traffic on a working path and the other ring (110) is for conducting the same user traffic on a protection path in the event of a failure in a communication link in the first ring on a protection path. A central node (300) is coupled to a plurality of nodes (312, 316, 320) to provide forwarding tables and updates to the nodes (312, 316, 320). As a result, IP traffic may be routed through the fiber optic ring network in a manner that provides fast switching from a working path to a protection path to minimize lost data packets whenever a communication link in the working path fails. Additionally, this capability is provided without requiring each node to have full IP routing capability. The forwarding tables (308) for the protection and working paths provide for path routes and forwarding for the packets on a packet by packet basis. Accordingly, a ring may serve as both a working path and a protection path according to the origin and destination of the data packets traveling thereon. Additionally, the central node (300) is adapted to generate multiple forwarding tables (308) to accommodate packet by packet forwarding in a network created to support virtual private networks. The forwarding tables (308) also are set up to support multicast transmissions of data packets.

1 aDantu, Ram1 aO'Connell, Pete uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20010314&DB=&locale=en_EP&CC=EP&NR=1083696A2&KC=A2&ND=401207nas a2200253 4500008004100000022001400041245007900055210006900134300001200203490000700215520044600222653002600668653002100694653002200715653002000737653002400757653001100781100001500792700002400807700001400831700001700845700002100862856007000883 1994 eng d a0045-790600aParallel algorithms for low-level vision on the homogeneous multiprocessor0 aParallel algorithms for lowlevel vision on the homogeneous multi a51 - 600 v203 a

In this work, we present the parallel implementation of three low-level vision algorithms, namely smoothing, histogram generation and edge detection by using the Sobel operator on the Homogeneous Multiprocessor. These algorithms were run on the simulator specifically developed for the Homogeneous Multiprocessor and the simulation experiments were used to establish the performance of these algorithms on the proposed architecture.

10aComputer architecture10aimage processing10aMIMO architecture10aMultiprocessing10apattern recognition10avision1 aDantu, Ram1 aDimopoulos, Nikitas1 aLi, Kinfu1 aPatel, Rajni1 aAl-Khalili, Asim uhttp://www.sciencedirect.com/science/article/pii/004579069490006X01457nas a2200181 4500008004100000022001400041245007800055210006900133260001200202300001200214490000600226520092700232100001501159700002401174700001701198700002101215856003901236 1992 eng d a1432-176900aDepth perception using blurring and its application in VLSI wafer probing0 aDepth perception using blurring and its application in VLSI wafe c12/1992 a35–450 v53 a

In this paper, we present a technique for measuring the amount of blur of an edge and using this information to determine the distance of a micromanipulator probe from a wafer surface in very large scale integration (VLSI) wafer probing. In this application, a soft and reliable touch of the probe with a metal pad in the wafer is a sensitive operation. The wafer is focused and several images of the probe while approaching the wafer are analyzed. In our theory, the amount of blur is calculated from the height of the step edge and the slope of the intensity profile at the zero crossing. Hence, our formula is simple and easy to use. We estimate the distance of the probe from the surface of the wafer and obtain a robust measure, i.e., one which is valid even in the presence of significant noise in the images. In order to validate our methods, we have experimented with various VLSI patterns as backgrounds.

1 aDantu, Ram1 aDimopoulos, Nikitas1 aPatel, Rajni1 aAl-Khalili, Asim uhttps://doi.org/10.1007/BF0121352801095nas a2200133 4500008004100000245004500041210004500086520071500131100001500846700001700861700002400878700002100902856003800923 1990 eng d00aVision Algorithms For VLSI Wafer Probing0 aVision Algorithms For VLSI Wafer Probing3 a

This paper deals with an important problem encountered in automating VLSI wafer probing. In this automation, vision is used for accurately guiding and lowering a probe to make contact with the wafer. In this paper, we discuss various algorithms used in measurement of the distance of the micro-manipulator from the wafer surface. In particular, we describe algorithms for alignment of consecutive frames of the wafer, separation of probe and wafer regions, and getting a clean image of the probe by eliminating traces of the background patterns. We also describe a three-level procedure for obtaining the proximity of the probe from the wafer. These algorithms are verified with the experimental data.

1 aDantu, Ram1 aPatel, Rajni1 aDimopoulos, Nikitas1 aAl-Khalili, Asim uhttps://doi.org/10.1117/12.96993402674nas a2200493 4500008004100000022001400041245004600055210004600101260001200147300001200159490000600171520129700177653002201474653003301496653002001529653001901549653002001568653003601588653003301624653002701657653001501684653003201699653001901731653003501750653002201785653001301807653001301820653001101833653001701844653003301861653001901894653001301913653002201926653003301948653000901981653001001990653001802000653001102018100001502029700002402044700001702068700002102085856007402106 1989 eng d a0894-650700aMicromanipulator vision for wafer probing0 aMicromanipulator vision for wafer probing c08/1989 a114-1170 v23 a

An overview is presented of a micromanipulator vision system for use in automating various functions during the testing of a wafer for semiconductor parameters and inspection of VLSI circuits. It is assumed that the wafer under test is not necessarily in its proper orientation. It is required that certain probes be lowered automatically onto certain pads to inject test vectors and to read the results for analysis. A methodology was developed for determining the position (especially the vertical distance from the target) of the tip of a probe, so that it can be guided accurately to its target pad. Standard image processing steps used for efficient feature extraction and registration of the target integrated circuit are outlined, and a method of obtaining the vertical distance of the tip of a probe from its target pad is presented. Two different criteria through which it can be established whether a probe is in contact with its target are given. The algorithm developed was tested for touch using different types of tips such as tungsten and tungsten carbide, and with NMOS and CMOS processes. Clean and accurate representations of the probes were extracted from integrated images in all the tests, and in all cases, touch was achieved without the surface being scratched

10aAutomatic testing10aautomating various functions10aCircuit testing10aCMOS processes10acomputer vision10acomputerised picture processing10aefficient feature extraction10aimage processing steps10aInspection10ainspection of VLSI circuits10aMachine vision10amicromanipulator vision system10aMicromanipulators10aNMOS ICs10aoverview10aProbes10aregistration10aSemiconductor device testing10aSystem testing10aTungsten10avertical distance10aVery large scale integration10aVLSI10aW tip10awafer probing10aWC tip1 aDantu, Ram1 aDimopoulos, Nikitas1 aPatel, Rajni1 aAl-Khalili, Asim uhttps://nsl.cse.unt.edu/content/micromanipulator-vision-wafer-probing01957nas a2200457 4500008004100000245005100041210004800092260000800140520062800148653002200776653002000798653002000818653002700838653003700865653001800902653001900920653002100939653002100960653002200981653001501003653003501018653003101053653001901084653001801103653002801121653002201149653001101171653001101182653002101193653003701214653003301251653001901284653001401303653000901317653001801326100001501344700002401359700001701383700002101400856007801421 1988 eng d00aA micro-manipulator vision in IC Manufacturing0 amicromanipulator vision in IC Manufacturing cApr3 a

An overview is presented of a micromanipulator vision system for use in automating various functions during the testing of a wafer for semiconducting parameters and inspection of VLSI circuits. Positioning the probe and touching a test pad are the chief concern of the work desired. A brief description of the experimental setup is given. The image processing techniques used in identifying and controlling the location of various components such as the probes and the test pads are discussed. The vision modules and an expert system using hierarchical plan generation to control the sequence of plans are included

10aAutomatic testing10aCircuit testing10acomputer vision10acomputer vision module10acomputerised pattern recognition10aexpert system10aexpert systems10aIC Manufacturing10aimage processing10aindustrial robots10aInspection10aintegrated circuit manufacture10aintegrated circuit testing10aMachine vision10aManufacturing10amicromanipulator vision10aMicromanipulators10aProbes10arobots10aSemiconductivity10aSemiconductor device manufacture10aSemiconductor device testing10aSystem testing10atest pads10aVLSI10awafer testing1 aDantu, Ram1 aDimopoulos, Nikitas1 aPatel, Rajni1 aAl-Khalili, Asim uhttps://nsl.cse.unt.edu/content/micro-manipulator-vision-ic-manufacturing