Linear Encryption Against Eavesdropping on Remote State Estimation

• 成果类型: Article
• 署名作者: Shang, Jun; Chen, Tongwen
• 署名单位: University of Alberta
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2022.3205548
• 发表日期: 2023
• 页码: 4413-4419
• 关键词: Eavesdropping; encryption; remote state estima-tion

摘要

This article considers the problem of eavesdropping on remote state estimation. Linear encryption strategies are used to protect the transmitted data. Two types of data transmission are considered: raw measurements generated by traditional sensors as well as innovations generated by smart sensors. For these two transmission scenarios, the encryption coefficients are obtained by formulating different optimization problems, with the target of maximizing the eavesdropper's estimation error covariance. For stable systems, the designed encryption strategies can effectively impair the eavesdropper's estimation performance. For unstable systems, the encryption can be designed to make the eavesdropper's estimation error covariance divergent. The encryption performance is evaluated through numerical simulations on both stable and unstable systems.