@conference {403, title = {Blockchain Based Authentication and Authorization Framework for Remote Collaboration Systems}, booktitle = {2019 IEEE 20th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM)}, year = {2019}, month = {June}, abstract = {

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.

}, keywords = {Access Control, authorization, blockchain, Digital Certificate, IoT, remote collaboration, Security}, doi = {10.1109/WoWMoM.2019.8792994}, author = {Widick, Logan and Ranasinghe, Ishan and Dantu, Ram and Jonnada, Srikanth} } @conference {382, title = {Performance Analysis of Elliptic Curves for Real-Time Video Encryption}, booktitle = {2018 National Cyber Summit (NCS)}, year = {2018}, month = {June}, abstract = {

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.

}, keywords = {Delays, ECC, Elliptic curve cryptography, encryption, Jitter, real-time systems, Real-time video streaming, Security, Streaming media}, doi = {10.1109/NCS.2018.00015}, author = {Sen, Nilanjan and Ram Dantu and Vempati, Jagannadh and Thompson, Mark} } @conference {270, title = {Prediction of human error using eye movements patterns for unintentional insider threat detection}, booktitle = {2018 IEEE 4th International Conference on Identity, Security, and Behavior Analysis (ISBA)}, year = {2018}, month = {Jan}, abstract = {

Threats from the inside of an organization{\textquoteright}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{\textquoteright}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{\textquoteright}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{\textquoteright} 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.

}, keywords = {accidental/unintentional incidents, Companies, eye, eye glasses, eye movement patterns, eye movements patterns, Feature extraction, Gaze tracking, Glass, human error prediction, insider security incidents, pupil feature extraction, Security, security of data, subjective mental workload, Task analysis, UIT detection, unintentional insider threat detection, Visualization}, doi = {10.1109/ISBA.2018.8311479}, author = {Takabi, Hassan and Hashem, Yassir and Ram Dantu} } @conference {262, title = {Optimized and Secured Transmission and Retrieval of Vital Signs from Remote Devices}, booktitle = {2017 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)}, year = {2017}, month = {July}, abstract = {

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{\textquoteright} 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.

}, keywords = {Brainpool curve, Cloud computing, confidential electronic personal health information, data transfer, decryption, Diffie-Hellman, Diseases, ECC algorithms, ECC curves, encryption, error prone, health care, healthcare professionals, Mobile communication, mobile device, mobile health, mobile networks, mobile phone platform, patient care, patient health information, patient health monitoring, patient vital data collection, Performance evaluation, public key cryptography, public key encryption algorithms, remote devices, remote monitoring, resource constrained mobile platforms, RSA, secured transmission, Security, servers, smart phones, smartphones, vital signs, WiFi}, doi = {10.1109/CHASE.2017.55}, author = {Thiyagaraja, Shanti and Ram Dantu and Shrestha, Pradhumna and Thompson, Mark and Smith, Christopher} } @conference {263, title = {Automating ECU Identification for Vehicle Security}, booktitle = {2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA)}, year = {2016}, month = {Dec}, abstract = {

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{\textquoteright}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.

}, keywords = {Acceleration, automobiles, automotive electronics, automotive security, Brakes, broadcasting, CAN bus, CAN bus messages, classification, consumer automobiles, control engineering computing, controller area network, controller area networks, ECU identification automation, electronic control unit, electronic engineering computing, embedded systems, learning (artificial intelligence), machine learning, machine learning classifier, pattern classification, Protocols, Security, security of data, Training, vehicle bus, vehicular ad hoc networks, vehicular cybersecurity, Wheels}, doi = {10.1109/ICMLA.2016.0111}, author = {Jaynes, Michael and Ram Dantu and Varriale, Roland and Evans, Nathaniel} } @article {94, title = {Neurokey: towards a new paradigm of cancelable biometrics-based key generation using electroencephalograms}, journal = {Computers \& Security}, year = {2016}, pages = {-}, abstract = {

\ 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{\textquoteright}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{\textquoteright}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 {\.I}I\} 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).

}, keywords = {Authentication, biometrics, cryptographic keys, cryptography, electroencephalograms, key generation, Security}, issn = {0167-4048}, doi = {http://dx.doi.org/10.1016/j.cose.2016.06.001}, url = {http://www.sciencedirect.com/science/article/pii/S0167404816300669}, author = {Bajwa, Garima and Ram Dantu} } @conference {233, title = {Pass-pic: A mobile user authentication}, booktitle = {Intelligence and Security Informatics (ISI), 2015 IEEE International Conference on}, year = {2015}, month = {May}, abstract = {

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.

}, keywords = {alphanumeric username, Authentication, key loggers, Keyboards, message authentication, mobile authentication, Mobile communication, mobile user authentication, pass-pic, passwords, pattern based passwords, picture based authentication system, PIN numbers, Random access memory, Security, smart phones, smudge attacks, Vibrations}, doi = {10.1109/ISI.2015.7165977}, author = {Bajwa, Garima and Ram Dantu and Aldridge, Ryan} } @conference {271, title = {PhD Forum: A System Identification Approach to Monitoring Network Traffic Security}, booktitle = {2015 IEEE 2nd International Conference on Cyber Security and Cloud Computing}, year = {2015}, month = {Nov}, abstract = {

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{\textquoteright}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.

}, keywords = {ARX, ARX model, autoregressive processes, Computational modeling, computer network security, Computer security, cyber system, dynamic system, Electronic mail, intrusion detection system, linear time invariant model, Mathematical model, Models, network traffic security, network traffic stability, Predictive models, Security, Silicon, System Identification, system identification approach, telecommunication traffic}, doi = {10.1109/CSCloud.2015.85}, author = {Mayo, Quentin and Bryce, Renee and Ram Dantu} } @conference {100, title = {Unintentional bugs to vulnerability mapping in Android applications}, booktitle = {Intelligence and Security Informatics (ISI), 2015 IEEE International Conference on}, year = {2015}, month = {May}, abstract = {

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.

}, keywords = {Android (operating system), Android applications, Android Lint, Androids, bugs, Computer bugs, Conferences, development phase, developmental loopholes, FindBugsTM, Humanoid robots, Indexes, invasive software, malware detection, many-to-many mapping matrix, mapping, matrix algebra, probability, probability mapping, program debugging, reverse mapping matrix, Security, security vulnerabilities, severity mapping, Software, software bug detection tool, software bugs, software tools, source code (software), source code analysis, unintentional behavior analysis, unintentional bugs, vulnerability, vulnerability mapping}, doi = {10.1109/ISI.2015.7165966}, author = {Bajwa, Garima and Fazeen, Mohamed and Ram Dantu and Tanpure, Sonal} } @article {226, title = {Security Issues in VoIP Telecommunication Networks}, journal = {Handbook on Securing Cyber-Physical Critical Infrastructure: Foundations and Challenges}, year = {2012}, pages = {763{\textendash}789}, abstract = {As 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.}, keywords = {P2P, Security, session initiation protocol, small world networks, telecommunications, voice over IP}, isbn = {978-0-12-415815-3}, doi = {https://doi.org/10.1016/B978-0-12-415815-3.00030-3}, url = {https://www.sciencedirect.com/science/article/pii/B9780124158153000303}, author = {Yang, Xiaohui and Ram Dantu and Wijesekera, Duminda} } @article {51, title = {A Testbed for Large Mobile Social Computing Experiments}, journal = {Int. J. Sen. Netw.}, volume = {8}, year = {2010}, pages = {89{\textendash}97}, abstract = {

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.

}, keywords = {context awareness, mobile communications, mobile computing, mobile devices, Privacy, Security, sensor information, sensors, smartphones, social computing, testbed, ubiquitous devices}, issn = {1748-1279}, doi = {10.1504/IJSNET.2010.034618}, url = {http://dx.doi.org/10.1504/IJSNET.2010.034618}, author = {Alazzawe, Ahmed and Alazzawe, Anis and Wijesekera, Duminda and Ram Dantu} } @article {37, title = {Nuisance Level of a Voice Call}, journal = {ACM Trans. Multimedia Comput. Commun. Appl.}, volume = {5}, year = {2008}, pages = {6:1{\textendash}6:22}, abstract = {

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.

}, keywords = {behavior, Multimedia communications, nuisance, presence, Security, tolerance, unwantedness}, issn = {1551-6857}, doi = {10.1145/1404880.1404886}, url = {http://doi.acm.org/10.1145/1404880.1404886}, author = {Kolan, Prakash and Ram Dantu and Cangussu, Jo{\~a}o} } @article {43, title = {VoIP Security: Attacks and Solutions}, journal = {Information Security Journal: A Global Perspective}, volume = {17}, year = {2008}, pages = {114{\textendash}123}, abstract = {

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.

}, keywords = {attack, defense mechanism, PSTN, Security, VoIP}, issn = {1939-3555}, doi = {10.1080/19393550802308618}, url = {http://dx.doi.org/10.1080/19393550802308618}, author = {Phithakkitnukoon, Santi and Ram Dantu and Baatarjav, Enkh-Amgalan} } @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 {14, title = {EAP Methods for Wireless Networks}, journal = {Comput. Stand. Interfaces}, volume = {29}, year = {2007}, pages = {289{\textendash}301}, keywords = {802.11, 802.16, EAP, Extensible authentication protocol, RFID, Security, WiMAX, Wireless LAN}, issn = {0920-5489}, doi = {10.1016/j.csi.2006.04.001}, url = {http://dx.doi.org/10.1016/j.csi.2006.04.001}, author = {Ram Dantu and Clothier, Gabriel and Atri, Anuj} }