@article {261, title = {Real-Time Mobile Device-Assisted Chest Compression During Cardiopulmonary Resuscitation}, journal = {American Journal of Cardiology}, volume = {120}, year = {2017}, pages = {196 - 200}, isbn = {0002-9149}, url = {http://dx.doi.org/10.1016/j.amjcard.2017.04.007}, author = {Sarma, Satyam and Bucuti, Hakiza and Chitnis, Anurag and Klacman, Alex and Ram Dantu} } @conference {264, title = {Realizing Optimal Chest Compression Fraction During Cardiopulmonary Resuscitation}, booktitle = {2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)}, year = {2016}, month = {June}, abstract = {

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.

}, keywords = {airways, Cardiac arrest, cardiopulmonary resuscitation, cardiovascular system, Chest Compression Fraction, CPR, CPR administrator switching, defibrillation, defibrillators, game theory, Games, Guidelines, Heart, lung, Measurement, optimal chest compression fraction, pneumodynamics, rational actor models}, doi = {10.1109/CHASE.2016.41}, author = {Talkington, Josh and Ram Dantu} } @conference {232, title = {Random anonymization of mobile sensor data: Modified Android framework}, booktitle = {Intelligence and Security Informatics (ISI), 2015 IEEE International Conference on}, year = {2015}, month = {May}, abstract = {

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.

}, keywords = {Accelerometers, Android, anonymized, application level, Data models, data privacy, Hidden Markov models, Mobile communication, mobile computing, mobile sensor data, mobile users, modified Android framework, operating system level, pervasive, Privacy, privacy concerns, provider, random anonymization, RANDSOM, RANDSOM framework, sensor data privacy, service providers, smart phone, smart phones, telecommunication security, third party applications}, doi = {10.1109/ISI.2015.7165968}, author = {Claiborne, Cynthia and Ncube, Cathy and Ram Dantu} } @conference {24, title = {Risk Management Using Behavior Based Bayesian Networks}, booktitle = {Proceedings of the 2005 IEEE International Conference on Intelligence and Security Informatics}, year = {2005}, publisher = {Springer-Verlag}, organization = {Springer-Verlag}, address = {Atlanta, GA}, 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 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).

}, isbn = {3-540-25999-6, 978-3-540-25999-2}, doi = {10.1007/11427995_10}, url = {http://dx.doi.org/10.1007/11427995_10}, author = {Ram Dantu and Kolan, Prakash} } @conference {11, title = {Risk Management Using Behavior Based Attack Graphs}, 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 = {

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).

}, isbn = {0-7695-2108-8}, url = {http://dl.acm.org/citation.cfm?id=977403.978389}, author = {Ram Dantu and Loper, Kall and Kolan, Prakash} } @article {229, title = {Requirements for Separation of IP Control and Forwarding}, year = {2003}, month = {11/2003}, publisher = {RFC Editor}, abstract = {

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.

}, author = {Anderson, Todd and Bowen, Ed and Ram Dantu and Doria, Avri and Gopal, Ram and Salim, Jamal and Khosravi, Hormuzd and Minhazuddin, Muneyb and Wasserman, Margaret} }