@article {415, title = {Detecting driver distraction using stimuli-response EEG analysis}, journal = {CoRR}, volume = {abs/1904.09100}, year = {2019}, url = {http://arxiv.org/abs/1904.09100}, author = {Bajwa, Garima and Fazeen, Mohamed and Dantu, Ram} } @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 {88, title = {A framework for secured collaboration in mHealth}, booktitle = {Collaboration Technologies and Systems (CTS), 2015 International Conference on}, year = {2015}, month = {06/2015}, abstract = {

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.

}, keywords = {cardiology, cardiopulmonary resuscitation, Cardiopulmonary resuscitation(CPR), Collaboration, Computers, CPR, health care, health care communication, human computer interaction, human-computer protocol, M2M network, machine to machine(M2M), Medical services, mHealth, Mobile communication, mobile computing, mobile health, Protocols, remote monitoring, Scalability, secure collaboration, secure emergency mobile health services, secured collaboration, security of data, servers, smart phones, smartphone}, doi = {10.1109/CTS.2015.7210450}, author = {Widick, Logan and Talkington, Josh and 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} } @article {231, title = {Quantifying Dynamic Cerebral Autoregulation using Electroencephalograms}, volume = {96}, year = {2015}, pages = {e69}, doi = {10.1016/j.apmr.2015.08.231}, author = {Bajwa, Garima and Ram Dantu and Nana, Arvind} } @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} } @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} } @conference {217, title = {NFC Based Two-Pass Mobile Authentication}, booktitle = {Research in Attacks, Intrusions, and Defenses: 16th International Symposium, RAID 2013, Rodney Bay, St. Lucia, October 23-25, 2013, Proceedings}, year = {2013}, publisher = {Springer}, organization = {Springer}, author = {Vempati, Jagannadh and Bajwa, Garima and Ram Dantu} } @booklet {234, title = {Self-Tracking via Brain-Mobile-Cloud Interface}, year = {2013}, abstract = {

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).

}, keywords = {Cerebral Blood Flow (CBF), Electroencephalography (EEG), Mobile cloud Interface, smart phone}, url = {http://www.aaai.org/ocs/index.php/SSS/SSS13/paper/view/5803}, author = {Bajwa, Garima and Ram Dantu and Fazeen, Mohamed and Joseph, Rajiv} }