Title: Building Secure-Aware Cyber-Physical Systems: A Satisfiability Modulo Convex Optimization Approach
Host: Ruzica Piskac
The rapidly increasing dependence on Cyber-Physical Systems (CPS) in building critical infrastructures—in the context of smart cities, power grids, medical devices, and self-driving cars—has opened the gates to increasingly sophisticated and harmful attacks with financial, societal, criminal or political effects. While a traditional cyber-attack may leak credit-card or other personal sensitive information, a CPS-attack can lead to a loss of control in nuclear reactors, gas turbines, the power grid, transportation networks, and other critical infrastructure, placing the Nation’s security, economy, and public safety at risk.
I will start this talk by motivating for the differences between CPS-security and cyber-security. To this end, I will show experimental results on non-invasive sensor spoofing attacks targeting the Anti-lock Brake Systems (ABS) in automobiles. As the need for CPS-security becomes evident, I will focus on a problem known as “secure state estimation.” It aims to estimate the state of a dynamical system when an adversary arbitrarily corrupts a subset of its sensors. Although of critical importance, this problem is NP-hard and combinatorial in nature since the subset of attacked sensors in unknown. I will show that the “secure state estimation” is a special case of a larger class of logic formulas, termed Satisfiability Modulo Convex (SMC) formulas. I will present then a new satisfiability modulo convex procedure that uses a lazy combination of Boolean satisfiability solving and convex programming to provide a satisfying assignment or determine that the formula is unsatisfiable. I will finish by showing, through multiple experimental and simulation results that SMC solvers outperform other techniques when used to solve the secure state estimation problem.
Yasser Shoukry is a Postdoctoral Scholar at the EECS Department at UC Berkeley, the EE Department at UCLA, and the ESE Department at UPenn. He received the Ph.D. in Electrical Engineering from the University of California at Los Angeles in 2015. Before joining UCLA, he spent four years as an R&D engineer in the industry of automotive embedded systems. His research interests include the design and implementation of secure- and privacy- aware cyber-physical systems and Internet of Things by drawing on tools from formal methods, embedded systems, control theory, and optimization theory.
Dr. Shoukry is the recipient of the Best Paper Award from the International Conference on Cyber-Physical Systems (ICCPS) in 2016. He is also the recipient of the UCLA EE Distinguished Ph.D. Dissertation Award in 2016, the UCLA Chancellors prize in 2011 and 2012, UCLA EE Graduate Division Fellowship in 2011 and 2012, and the UCLA EE Preliminary Exam Fellowship in 2012. In 2015, Dr. Shoukry led the UCLA/Caltech/CMU team to win the first place in the NSF Early Career Investigators (NSF-ECI) research challenge. His team represented the NSF-ECI in the NIST Global Cities Technology Challenge, an initiative designed to advance the deployment of Internet of Things (IoT) technologies within a smart city.