Detection and Identification of Sparse Sensor Attacks in Cyber-Physical Systems With Side Information

This article investigates the attack detection and identification problem for cyber-physical systems under sparse sensor attacks. A novel candidate set construction algorithm, where only partial combinations of different channels are checked, is proposed to efficiently generate the candidate set containing all the possible sets of corrupted channels under stealthy attacks. Besides, through introducing a unified attack model that precisely characterizes the attack performance and stealthiness, necessary and sufficient conditions for the existence of undetectable/unidentifiable attacks are proposed. Based on the obtained conditions, a novel attack detection and identification strategy is proposed. Compared with the existing methods focusing only on the measurements, more attacks can be detected/identified through introducing side information and the reliability of detector is enhanced through making full use of the attack performance analysis result. Finally, a numerical simulation is provided to illustrate the correctness and effectiveness of the proposed conditions and methods.