SYMay 21, 2018
Detection of Sensor Attack and Resilient State Estimation for Uniformly Observable Nonlinear Systems having Redundant SensorsJunsoo Kim, Chanhwa Lee, Hyungbo Shim et al.
This paper presents a detection algorithm for sensor attacks and a resilient state estimation scheme for a class of uniformly observable nonlinear systems. An adversary is supposed to corrupt a subset of sensors with the possibly unbounded signals, while the system has sensor redundancy. We design an individual high-gain observer for each measurement output so that only the observable portion of the system state is obtained. Then, a nonlinear error correcting problem is solved by collecting all the information from those partial observers and exploiting redundancy. A computationally efficient, on-line monitoring scheme is presented for attack detection. Based on the attack detection scheme, an algorithm for resilient state estimation is provided. The simulation results demonstrate the effectiveness of the proposed algorithm.
SYMay 7, 2018
On Redundant Observability: From Security Index to Attack Detection and Resilient State EstimationChanhwa Lee, Hyungbo Shim, Yongsoon Eun
The security of control systems under sensor attacks is investigated. Redundant observability is introduced, explaining existing security notions including the security index, attack detectability, and observability under attacks. Equivalent conditions between redundant observability and existing notions are presented. Based on a bank of partial observers utilizing Kalman decomposition and a decoder exploiting redundancy, an estimator design algorithm is proposed enhancing the resilience of control systems. This scheme substantially improves computational efficiency utilizing far less memory.