@conference {522, title = {Can{\textquoteright}t Understand SLAs? Use the Smart Contract}, booktitle = {2021 Third IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)}, year = {2021}, publisher = {IEEE}, organization = {IEEE}, address = {Atlanta, GA, USA}, abstract = {

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.

}, keywords = {ambiguity, ambiguity index, blockchain, clauses, complexity, Ethereum, interpretations, machine learning, service level agreement, SLA, smart contract, smart legal contract}, isbn = {978-1-6654-1623-8}, doi = {10.1109/TPSISA52974.2021.00015}, url = {https://ieeexplore.ieee.org/abstract/document/9750250}, author = {Upadhyay, Kritagya and Dantu, Ram and He, Yanyan and Badruddoja, Syed and Salau, Abiola} } @conference {523, title = {A Collaborative and Adaptive Feedback System for Physical Exercises}, booktitle = {2021 IEEE 7th International Conference on Collaboration and Internet Computing (CIC)}, year = {2021}, publisher = {IEEE}, organization = {IEEE}, address = {Atlanta, GA, USA}, abstract = {

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.

}, keywords = {Distributed Machine Learning, Human-Computer Interaction, Pose Estimation, Reinforcement Learning}, isbn = {978-1-6654-1625-2}, doi = {10.1109/CIC52973.2021.00012}, url = {https://ieeexplore.ieee.org/abstract/document/9707166}, author = {Ranasinghe, Ishan and Yuan, Chengping and Dantu, Ram and Albert, Mark V.} } @conference {543, title = {Cyber-Physiotherapy: Rehabilitation to Training}, booktitle = {2021 IFIP/IEEE International Symposium on Integrated Network Management (IM)}, year = {2021}, publisher = {IEEE}, organization = {IEEE}, address = {Bordeaux, France}, abstract = {

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.

}, keywords = {Fitts{\textquoteright}s law, Human-Computer Interaction, Index of Difficulty, Pose Estimation, Reinforcement Learning}, isbn = {978-3-903176-32-4}, url = {https://ieeexplore.ieee.org/abstract/document/9464036}, author = {Ranasinghe, Ishan and Dantu, Ram and Albert, Mark V. and Watts, Sam and Ocana, Ruben} } @conference {397, title = {CMCAP: Ephemeral Sandboxes for Adaptive Access Control}, booktitle = {Proceedings of the 24th ACM Symposium on Access Control Models and Technologies}, year = {2019}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {adaptive access control, ephemeral sandboxes, information flow control, intrusion prevention, runtime containment}, isbn = {978-1-4503-6753-0}, doi = {10.1145/3322431.3325414}, url = {http://doi.acm.org/10.1145/3322431.3325414}, author = {Bucuti, Theogene and Dantu, Ram and Morozov, Kirill} } @conference {346, title = {Cyber Handyman and Nursing for Humanitarian Services and Disaster Relief}, booktitle = {2018 IEEE International Symposium on Technologies for Homeland Security (HST)}, year = {2018}, month = {Oct}, abstract = {

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.

}, keywords = {Collaboration, collaboration system, common grounding, Complexity theory, Entropy, Grounding, helper-worker collaboration, human-human collaboration, human-machine collaboration, protocol complexity theory, Protocols, remote collaboration, Senior citizens, Task analysis, voice over IP}, doi = {10.1109/THS.2018.8574176}, author = {Jonnada, Srikanth and Ram Dantu and Ranasinghe, Ishan} } @conference {74, title = {Context-aware Multimedia Encryption in Mobile Platforms}, booktitle = {Proceedings of the 9th Annual Cyber and Information Security Research Conference}, year = {2014}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, abstract = {

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.

}, keywords = {Android, context-aware, encryption, speech recognition, VoIP}, isbn = {978-1-4503-2812-8}, doi = {10.1145/2602087.2602115}, url = {http://doi.acm.org/10.1145/2602087.2602115}, author = {Fazeen, Mohamed and Bajwa, Garima and Ram Dantu} } @conference {87, title = {Cerebral Autoregulation Assessment Using Electroencephalograms}, booktitle = {Proceedings of the 8th International Conference on Body Area Networks}, year = {2013}, publisher = {ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering)}, organization = {ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering)}, address = {ICST, Brussels, Belgium, Belgium}, abstract = {

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.

}, keywords = {Blood pressure, cerebral autoregulation, cerebral blood flow, electroencephalograms}, isbn = {978-1-936968-89-3}, doi = {10.4108/icst.bodynets.2013.253703}, url = {http://dx.doi.org/10.4108/icst.bodynets.2013.253703}, author = {Bajwa, Garima and Ram Dantu} } @article {15, title = {Cuffless Differential Blood Pressure Estimation Using Smart Phones}, journal = {IEEE Transactions on Biomedical Engineering}, volume = {60}, year = {2013}, pages = {1080 - 1089}, abstract = {

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{\textendash}100\% accuracy.

}, keywords = {Blood pressure, cuffless, Estimation, finger pulse, Heart, Microphones, mobile camera, Mobile communication, mobile phone, Synchronization, Valves, vascular transit time}, doi = {10.1109/TBME.2012.2211078}, author = {Chandrasekaran, Vikram and Ram Dantu and Jonnada, Srikanth and Thiyagaraja, Shanti and Subbu, Kalyan} } @conference {101, title = {Current and Future Trends in Social Media}, booktitle = {2011 IEEE Third Int{\textquoteright}l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int{\textquoteright}l Conference on Social Computing}, year = {2011}, abstract = {

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.

}, keywords = {Buildings, Electronic mail, Facebook, Media, Online Social Networks, Privacy, Social Media, Social Network Trends, Twitter}, doi = {10.1109/PASSAT/SocialCom.2011.125}, author = {Baatarjav, Enkh-Amgalan and Ram Dantu} } @article {44, title = {ContextAlert: Context-aware alert mode for a mobile phone}, journal = {International Journal of Pervasive Computing and Communications}, volume = {6}, year = {2010}, month = {Sep}, pages = {1{\textendash}23}, abstract = {

Purpose {\textendash} 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{\textquoteright}s context. The purpose of this paper is to present a context-aware mobile computing model (ContextAlert) that senses the user{\textquoteright}s context and intelligently configures the mobile phone alert mode accordingly. Design/methodology/approach {\textendash} 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 {\textendash} 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 {\textendash} 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{\textquoteright}s context than having various sensors attached to different parts of user{\textquoteright}s body; second, by being a novel model that uses sensed contextual information to provide a service that better synchronizes the user{\textquoteright}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.

}, issn = {1742-7371}, doi = {10.1108/17427371011084266}, author = {Phithakkitnukoon, Santi and Ram Dantu} } @conference {59, title = {Change Point Detection Based on Call Detail Records}, booktitle = {Proceedings of the 2009 IEEE International Conference on Intelligence and Security Informatics}, year = {2009}, publisher = {IEEE Press}, organization = {IEEE Press}, address = {Piscataway, NJ, USA}, abstract = {

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.

}, isbn = {978-1-4244-4171-6}, url = {http://dl.acm.org/citation.cfm?id=1706428.1706438}, author = {Zhang, Huiqi and Ram Dantu and Cangussu, Jo{\~a}o} } @conference {99, title = {Call Algebra}, booktitle = {2008 5th IEEE Consumer Communications and Networking Conference}, year = {2008}, month = {Jan}, abstract = {

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.

}, keywords = {Algebra, call algebra, caller-callee matrices, communication pattern, Computer science, Context modeling, Filtering, Humans, Internet telephony, IP networks, IP telephony problem, matrix algebra, Mood, Peer to peer computing, social aspects of automation, social group, Social network services, voice-over-IP, VoIP network}, doi = {10.1109/ccnc08.2007.199}, author = {Kolan, Prakash and Ram Dantu} } @article {71, title = {Classification of phishers}, journal = {Journal of Homeland Security and Emergency Management}, volume = {5}, year = {2008}, abstract = {

Phishing attackers masquerade as genuine senders and try to steal consumers{\textquoteright} 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{\textquoteright}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{\textquoteright} social network. Considering such issues, we based our solution on the trustworthiness of the relays participating in routing the emails. We examine the email{\textquoteright}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{\textquoteright}s "subject" before adding the email to the inbox.

}, keywords = {application security, network security, phishing, spam}, author = {Ram Dantu and Palla, Srikanth and Cangussu, Jo{\~a}o} } @conference {50, title = {CPL: Enhancing Mobile Phone Functionality by Call Predicted List}, booktitle = {Proceedings of the OTM Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: 2008 Workshops: ADI, AWeSoMe, COMBEK, EI2N, IWSSA, MONET, OnToContent + QSI, ORM, PerSys, RDDS, SEMELS, and SWWS}, year = {2008}, publisher = {Springer-Verlag}, organization = {Springer-Verlag}, address = {Berlin, Heidelberg}, abstract = {

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{\textquoteright}s call history to build a probabilistic model of calling behavior based on the caller{\textquoteright}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.

}, keywords = {Call prediction, Context-aware computing, mobile phone}, isbn = {978-3-540-88874-1}, doi = {10.1007/978-3-540-88875-8_80}, url = {http://dx.doi.org/10.1007/978-3-540-88875-8_80}, author = {Phithakkitnukoon, Santi and Ram Dantu} } @conference {34, title = {Classification of Attributes and Behavior in Risk Management Using Bayesian Networks}, booktitle = {2007 IEEE International Conference on Intelligence and Security Informatics (ISI) }, year = {2007}, month = {05/2007}, address = {New Brunswick, NJ}, abstract = {

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{\textquoteright} 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.

}, keywords = {attack behaviour, attack graphs, attack intent, Bayesian network, behavior, belief networks, explorer behavior, hacker behavior, opportunist behavior, profile behavioral resource classification, risk management, Security, security administration, vulnerability analysis}, doi = {10.1109/ISI.2007.379536}, author = {Ram Dantu and Kolan, Prakash and Akl, Robert and Loper, Kall} } @article {176, title = {CISE and Global Implications}, year = {2006}, month = {06/2006}, publisher = {NSF Workshop on Computing Research Infrastructure}, address = {Snowbird, Utah}, author = {Ram Dantu} } @conference {66, title = {Collaborative Vision Using Networked Sensors}, booktitle = {Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC{\textquoteright}04) Volume 2 - Volume 2}, year = {2004}, publisher = {IEEE Computer Society}, organization = {IEEE Computer Society}, address = {Washington, DC, USA}, abstract = {

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

}, isbn = {0-7695-2108-8}, url = {http://dl.acm.org/citation.cfm?id=977403.978444}, author = {Ram Dantu and Joglekar, Sachin} } @article {279, title = {Constraint-Based Label Switched Path Setup using Label Distribution Protocol}, year = {2002}, url = {https://tools.ietf.org/html/rfc3212}, author = {Andersson, Loa and Callon, Ross and Ram Dantu and Doolan, Paul and Feldman, Nancy and Fredette, Andre and Gray, Eric and Heinanen, Juha and Jamoussi, Bilel and Kilty, Timothy and Malis, Andrew and Girish, Muckai and Worster, Tom and Wu, Liwen} }