A Resilient Distributed Kalman Filtering Under Bidirectional Stealthy Attack

Abstract

False data injection attacks are widely investigated to exploit the cyber-vulnerability of Cyber-Physical System. However, the existing attack policies only consider the cyber-vulnerability in the one-way communication channel. In this letter, a bidirectional stealthy false data injection attack is proposed to bypass the hostile data detector and degrade the estimation performance in the distributed Kalman filtering system. The stealthiness and the influence of the bidirectional stealthy attack is demonstrated by the theoretical analysis. Furthermore, the alternate transmission protocol is proposed to prevent the bidirectional stealthy attack policy. To remedy the protocol and improve the detection sensitivity, an attack detector with multiple factors is proposed. Besides, the choosing principle of the detection factors is analyzed. Simulation examples are presented to investigate the bidirectional stealthy attack and the developed estimator.