Optimal Linear Cyber-Attack on Remote State Estimation
报告题目：Optimal Linear Cyber-Attack on Remote State Estimation
Abstract: We consider malicious cyber attacks in a remote state estimation application where a smart sensor node transmits data to a remote estimator equipped with a false data detector. It is assumed that all the sensor data can be observed and modified by the malicious attacker and a residue-based detection algorithm is used at the remote side to detect data anomalies. We propose a linear deception attack strategy and present the corresponding feasibility constraint which guarantees that the attacker is able to successfully inject false data without being detected. The evolution of the estimation error covariance at the remote estimator is derived and the degradation of system performance under the proposed linear attack policy is analyzed. Furthermore, we obtain a closed-form expression of the optimal attack strategy among all linear attacks. Comparison of attack strategies through simulated examples are provided.
Ling Shi received the B.S. degree in electrical and electronic engineering from Hong Kong University of Science and Technology, Kowloon, Hong Kong, in 2002 and the Ph.D. degree in Control and Dynamical Systems from California Institute of Technology, Pasadena, CA, USA, in 2008. He is currently an associate professor at the Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology. His research interests include cyber-physical systems security, networked control systems, sensor scheduling, and event-based state estimation. He has been serving as a subject editor for International Journal of Robust and Nonlinear Control from March 2015 and an associate editor for IEEE Transactions on Control of Network Systems from July 2016. He also served as an associate editor for a special issue on Secure Control of Cyber Physical Systems in the IEEE Transactions on Control of Network Systems in 2015-2016.