Consensus-based distributed secure state estimation for cyber-physical systems against random cyber attacks

Security issues of cyber–physical systems (CPSs) have attracted extensive attention due to the increasing vulnerability to malicious threats from cyber attacks. This paper focuses on the problem of consensus-based distributed secure state estimation for CPSs against cyber attacks. A novel cyber attack mode is established with high randomness. Specifically, the attack is randomly set up in attack position, type, duration and value, and can cause significant devastation due to the stochastic and unpredictable attack characteristics. To counter such attack behavior, a consensus-based distributed secure state estimation with a compensation-based measurement is proposed. The compensation-based measurement, obtained by combining an attack detector and prediction measurement, is utilized to replace the current measurement in the attacked channel. In the consensus-based distributed secure state estimation algorithm, the distributed estimators first adopt the compensation-based measurement to perform the local information fusion estimation, and then use the transmitted estimates to realize the consensus estimation. Furthermore, the information fusion estimator is recursively derived, and a sufficient condition is provided based on the Lyapunov method to provide the convergence of the consensus estimation. Finally, a series of numerical simulations are provided to illustrate the effectiveness of the proposed method.