Optimal innovation-based deception attacks with side information against remote state estimation in cyber-physical systems

Abstract

In this paper, the problem of designing the optimal deception attacks against the remote state estimation in cyber-physical systems is investigated in the scenario where the attacker has the ability to acquire the side information about the system by employing an extra sensor. To degenerate the remote estimation performance, the attacker replaces the transmitted signals with the combination of the innovations from the system sensor and the extra sensor. Under the proposed attacks, the recursion of the error covariance of the remote estimates is derived by utilizing the orthogonality principle and the statistical properties of the related random variables. Then, the design of the attacks is transformed into a quadratic multivariate optimization problem and the optimal distribution of the modified innovations is found by taking advantage of the Lagrange multiplier method. Based on this, it is proved that the optimal policy is the solution to a semi-definite programming (SDP) problem, which results in the largest estimation errors and maintains the deceptiveness concurrently. Finally, simulation examples are given to verify the effectiveness of this work.