窃听攻击下基于传感器传输策略的信息物理系统隐私保护

The openness of cyber-physical systems (CPS) and the widespread use of wireless sensors elevate the vulnerability to eavesdropping attacks on CPS. Consequently, the privacy preservation of CPS becomes an urgent and critical concern. In this paper, a sensor transmission strategy combining transmission scheduling and noise injection is designed using the remote state estimation method to protect the privacy of CPS under eavesdropping attacks. This strategy enables the sensor to transmit data or maintain silence, utilizing noise transmission to confuse the data when sending it. This paper introduces the concept of open-loop prediction as the system reference. It constructs Markov chain models for the legitimate user and eavesdropper, deriving the expected steady-state estimation error covariance. Consequently, the range of noise transmission probability is determined. The objective is to minimize the error of the legitimate user while maintaining the error of the eavesdropper above the open-loop estimation, thereby striking a balance between privacy protection and energy management. In addition, the proposed scheme is demonstrated to possess a threshold structure, and its effectiveness is validated and analyzed within a simulation environment by a dynamic programming algorithm.