Optimal Privacy-Preserving Transmission Schedule Against Eavesdropping Attacks on Remote State Estimation

被引：3

作者：

Zou, Jiaying ^{[1
,2
]}

Liu, Hanxiao ^{[1
,2
]}

Liu, Chun ^{[3
]}

Ren, Xiaoqiang ^{[3
]}

Wang, Xiaofan ^{[3
]}

机构：

[1] Shanghai Univ, Sch Future Technol, Shanghai 200444, Peoples R China

[2] Shanghai Univ, Inst Artificial Intelligence, Shanghai 200444, Peoples R China

[3] Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai 200444, Peoples R China

来源：

IEEE CONTROL SYSTEMS LETTERS | 2024年 / 8卷

基金：

中国国家自然科学基金;

关键词：

Noise; Eavesdropping; Optimal scheduling; Estimation error; State estimation; Schedules; Job shop scheduling; Cyber-physical systems; remote state estimation; eavesdropping attacks; transmission schedule;

D O I：

10.1109/LCSYS.2024.3398200

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This letter is concerned with the preservation of privacy in remote state estimation of cyber-physical systems. A privacy-preserving transmission scheduling strategy against eavesdropping is proposed, incorporating three operational modes for sensors: silence, direct transmission, and noise-injected transmission. This strategy is designed to minimize the transmission cost and estimation error covariance for the remote estimator while maximizing the estimation error covariance for eavesdroppers. Threshold structures are demonstrated for optimal transmission schedules in different scenarios. Additionally, a novel correlation between the optimal transmission choice and the magnitude of injection noise is presented, particularly pertinent to scenarios involving direct transmission and transmission with injection noise. This correlation is important in balancing transmission information integrity against privacy concerns. Finally, several numerical examples are presented to demonstrate the effectiveness of the theoretical results.

引用

页码：538 / 543

页数：6

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