Residual-Based False Data Injection Attacks Against Multi-Sensor Estimation Systems

• Published in: IEEE/CAA journal of automatica sinica Vol. 10; no. 5; pp. 1181 - 1191
• Main Authors: Guo, Haibin, Sun, Jian, Pang, Zhong-Hua
• Format: Journal Article
• Language: English
• Published: Piscataway Chinese Association of Automation (CAA) 01.05.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); Beijing Institute of Technology Chongqing Innovation Center,Chongqing 401120,China%Key Laboratory of Fieldbus Technology and Automation of Beijing,North China University of Technology,Beijing 100144; National Key Laboratory of Autonomous Intelligent Unmanned Systems,School of Automation,Beijing Institute of Technology,Beijing 100081,China%National Key Laboratory of Autonomous Intelligent Unmanned Systems,School of Automation,Beijing Institute of Technology,Beijing 100081,China
• Subjects: Convexity; Covariance; Current measurement; Cyber-physical systems; Cyber-physical systems (CPSs); Detectors; Estimation error; false data injection (FDI) attacks; Optimization; Remote sensors; remote state estimation; Sensor systems; Simulation; stealthy attacks; System performance; remote state estimation; Cyber-physical systems(CPSs); false data injection(FDI)attacks; stealthy attacks
• ISSN: 2329-9266; 2329-9274
• DOI: 10.1109/JAS.2023.123441

This paper investigates the security issue of multi-sensor remote estimation systems. An optimal stealthy false data injection (FDI) attack scheme based on historical and current residuals, which only tampers with the measurement residuals of partial sensors due to limited attack resources, is proposed to maximally degrade system estimation performance. The attack stealthiness condition is given, and then the estimation error covariance in compromised state is derived to quantify the system performance under attack. The optimal attack strategy is obtained by solving several convex optimization problems which maximize the trace of the compromised estimation error covariance subject to the stealthiness condition. Moreover, due to the constraint of attack resources, the selection principle of the attacked sensor is provided to determine which sensor is attacked so as to hold the most impact on system performance. Finally, simulation results are presented to verify the theoretical analysis.