BEGIN:VCALENDAR BEGIN:VEVENT SUMMARY:CS Colloquium: Yevgeniy Vorobeychik (Vanderbilt U) - Cyber Games: Attack Plan Interdiction and Adversarial Machine Learning DESCRIPTION:Speaker: Yevgeniy Vorobeychik, Vanderbilt University Talk Title: Cyber Games: Attack Plan Interdiction and Adversarial Machine Learning Series: CS Colloquium Abstract: Over the last few years I have been working on game theoretic models of security, with a particular emphasis on issues salient in cyber security. In this talk I will give an overview of some of this work. I will first spend some time motivating game theoretic treatment of problems relating to cyber and describe some important modeling considerations. In the remainder, I will describe two game theoretic models, and associated solution techniques and analyses. The first is the "optimal attack plan interdiction" problem. In this model, we view a threat formally as a sophisticated planning agent, aiming to achieve a set of goals given some specific initial capabilities and considering a space of possible "attack actions/vectors" that may (or may not) be used towards the desired ends. The defender's goal in this setting is to "interdict" a select subset of attack vectors by optimally choosing among mitigation options in order to prevent the attacker from being able to achieve its goals. I will describe the formal model, explain why it is challenging, and present highly scalable decomposition-based integer programming techniques that leverage extensive research into heuristic planning in AI. The second model addresses the problem of using machine learning to separate malware from goodware, where an adversary actively attempts to circumvent the resulting classifier. I will show how to formulate the problem of computing optimal randomized defense in this setting as a linear program which accounts both for adversarial response and operational constraints. Finally, I will show that our approach outperforms state of the art on several metrics. Biography: Yevgeniy Vorobeychik is an Assistant Professor of Computer Science and Computer Engineering at Vanderbilt University. Previously (2010-2013), he was a Member of Technical Staff at Sandia National Laboratories. Between 2008 and 2010 he was a post-doctoral research associate at the University of Pennsylvania Computer and Information Science department. He received Ph.D. (2008) and M.S.E. (2004) degrees in Computer Science and Engineering from the University of Michigan, and a B.S. degree in Computer Engineering from Northwestern University. His work focuses on game theoretic modeling of security, algorithmic and behavioral game theory and incentive design, optimization, complex systems, epidemic control, network economics, and machine learning. Dr. Vorobeychik has published over 50 research articles on these topics. Dr. Vorobeychik was nominated for the 2008 ACM Doctoral Dissertation Award and received honorable mention for the 2008 IFAAMAS Distinguished Dissertation Award. In 2012 he was nominated for the Sandia Employee Recognition Award for Technical Excellence. He was also a recipient of a NSF IGERT interdisciplinary research fellowship at the University of Michigan, as well as a distinguished Computer Engineering undergraduate award at Northwestern University. Host: Teamcore Group DTSTART:20140303T130000 LOCATION:RTH 306 URL;VALUE=URI: DTEND:20140303T143000 END:VEVENT END:VCALENDAR