State estimation of CPSs with deception attacks: Stability analysis and approximate computation

Abstract This paper is concerned with the state estimation problems of cyber-physical systems (CPSs) under unobservable deception attacks. First, the optimal state estimator is provided based on the derived state probability density function, which consists of an exponentially increasing number of linear Gaussian hypotheses. The exponentially growing number of components will lead to high computational cost. Therefore, a suboptimal state estimator based on the IMM algorithm is proposed, which is computationally more efficient than the optimal estimator. Finally, numerical results are given to verify the effectiveness and superiority of the proposed suboptimal estimator, rendering an efficient and stable state estimation when the privacy of sensor measurements is attacked.