Optimal Transmission Schedule With Privacy Preservation for Cyber-Physical System Against Eavesdropping Attack

Abstract

Privacy issues in remote state estimation for Cyber-Physical System (CPS) against eavesdropping attack pose significant challenges in ensuring both system performance and data security. Existing studies often overlook the challenges posed by the acknowledgment signal's potential risks and the asymptotic convergence properties of stable systems. To address these challenges, this paper proposes a privacy-preserving optimal transmission scheduling method based on a pre-arranged indicator. The method determines whether to transmit real state estimates or artificial noise by solving an optimization problem that balances estimation performance and privacy preservation. The privacy is ensured by keeping the eavesdropper's estimation error covariance higher than the legitimate estimator's. A threshold structure is proved with theoretical derivations. Simulation results are given to support the theoretical analysis.