- April 09, 2018
- 4:00 p.m.
- 260 New Classroom Building
- Dr. Tanmay Rajpurohit, Georgia Tech
Abstract: Recent cyber physical attacks like “Stuxnet Attack” ( which resulted in a complex malware infecting uranium enrichment facilities in Iran and causing damage to approximately 1000 centrifuges at these plants in 2010) or “Aurora Attack” (took place in March 2007 by researchers investigating supervisory control and data acquisition (SCADA) system vulnerabilities at utility companies) has motivated researchers in diverse areas to look beyond cryptographic security and use alternative techniques to enhance security of communication networks and systems, and CPS and their underlying networked control systems. The techniques are include but are not limited to Game-theoretic security, Information-theoretic security, Control-theoretic cyber-physical security, etc. In this work, we addressed stochastic game theory based approach that treats the true controller and the adversary/attacker as competitive decision makers. We consider a two-player stochastic differential game problem on an infinite time horizon where the players invoke controller and stopper strategies on a nonlinear stochastic differential game problem driven by Brownian motion. The optimal strategies for the two players are given explicitly by exploiting connections between stochastic Lyapunov stability theory and stochastic Hamilton-Jacobi-Isaacs theory. In particular, we show that asymptotic stability in probability of the differential game problem is guaranteed by means of a Lyapunov function which can clearly be seen to be the solution to the steady-state form of the stochastic Hamilton-Jacobi-Isaacs equation, and hence, guaranteeing both stochastic stability and optimality of the closed-loop control and stopper policies.
Bio: Tanmay Rajpurohit received the B. Tech. degree in aerospace engineering from the Indian Institute of Technology, Bombay, India, in 2001, the M.S. degree in aerospace engineering from Georgia Tech, Atlanta, GA, in 2002, and the M.A. degree in economics from New York University, New York, NY, in 2005. In 2005 he returned to India to bolster the Nation's manufacturing and engineering sector. In 2013 he returned to the US to pursue his doctoral degree in aerospace engineering from Georgia Tech. In the interim he received the M.S. degree in applied mathematics from Georgia Tech in 2016 and the M.S. degree in computer science specializing in machine learning from Georgia Tech in 2018 as well as PhD degree in aerospace engineering from Georgia Tech in 2018. During his doctoral studies he taught two junior year courses as a course instructor and awarded with outstanding graduate student instructor for the aerospace engineering. His research interests include analysis and control of nonlinear systems, stochastic systems, adaptive control, thermodynamics, mathematical finance, and differential games.