Optimal linear attack for multi-sensor network against state estimation. Issue 16 (November 2022)

• Record Type: Journal Article
• Authors: Li, Tenghui; Wang, Zhuping; Huang, Chao; Zhang, Hao
• Is Part Of: Journal of the Franklin Institute. Volume 359:Issue 16(2022)
• Page Start: 9220
• Page End: 9240
• Publication Date: 2022-11
• Subjects: Science -- Periodicals; Technology -- Periodicals; Patents -- United States -- Periodicals; 505
• DOI: 10.1016/j.jfranklin.2022.07.024
• Languages: English
• ISSNs: 0016-0032

Abstract

Abstract: This paper is concerned with a security problem about malicious integrity attacks in state estimation system, in which multiple smart sensors locally measure information and transmit it to a remote fusion estimator though wireless channels. A joint constraint is considered for the attacker behaviour in each channel to keep stealthiness under a residual-based detector on the remote side. In order to degrade the estimator performance, the attacker will maximize the trace of the remote state estimation error covariance which is derived based on Kalman filter theory. It is proved that the optimal linear attack strategy design problem is convex and finally turned into a semi-definite programming problem. In addition, the tendency of attack behaviour on recursive and fixed Kalman filter system is analyzed. Several examples are given to illustrate the theoretical results.