Analysis of Stealthy False Data Injection Attacks Against Networked Control Systems: Three Case Studies

• Published in: Journal of systems science and complexity Vol. 36; no. 4; pp. 1407 - 1422
• Main Authors: Pang, Zhonghua, Fu, Yuan, Guo, Haibin, Sun, Jian
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2023; Springer Nature B.V
• Subjects: Closed loops; Complex Systems; Control; Control systems; Feedback control; Kalman filters; Mathematics; Mathematics and Statistics; Mathematics of Computing; Network control; Operations Research/Decision Theory; Statistics; Systems Theory; False data injection attack; networked control systems (NCSs); stability; stealthiness
• ISSN: 1009-6124; 1559-7067
• DOI: 10.1007/s11424-022-2120-6

This paper mainly investigates the security problem of a networked control system based on a Kalman filter. A false data injection attack scheme is proposed to only tamper the measurement output, and its stealthiness and effects on system performance are analyzed under three cases of system knowledge held by an attacker and a defender. Firstly, it is derived that the proposed attack scheme is stealthy for a residual-based detector when the attacker and the defender hold the same accurate system knowledge. Secondly, it is proven that the proposed attack scheme is still stealthy even if the defender actively modifies the Kalman filter gain so as to make it different from that of the attacker. Thirdly, the stealthiness condition of the proposed attack scheme based on an inaccurate model is given. Furthermore, for each case, the instability conditions of the closed-loop system under attack are derived. Finally, simulation results are provided to test the proposed attack scheme.