Secure Recursive State Estimation of Networked Systems Against Eavesdropping: A Partial-Encryption-Decryption Method

• 成果类型: Article
• 署名作者: Zou, Lei; Wang, Zidong; Shen, Bo; Dong, Hongli
• 署名单位: Donghua University; Brunel University; Northeast Petroleum University
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2024.3512413
• 发表日期: 2025
• 页码: 3681-3694
• 关键词: Cryptography; encryption; computational efficiency; Information Security; State estimation; noise; vectors; Transmitters; Eavesdropping; Noise measurement; encryption-decryption scheme (EDS); minimum mean squared error (MMSE); recursive state estimation (RSE); ultimate boundedness analysis

摘要

This article addresses the problem of secure recursive state estimation for a networked linear system, which may be vulnerable to interception of transmitted measurement data by eavesdroppers. To effectively protect information security, an encryption-decryption-based communication scheme can be used, but encrypting all the measurement data from sensors can result in significant computational costs. To address this issue, a partial-encryption-decryption (PED) mechanism is proposed to enhance information security with relatively low computational costs. In this mechanism, only part of the transmitted measurement signals are encrypted, and the remaining signals are transmitted directly to the estimator. A Jordan-canonical-form-based approach is developed to select the appropriate parameter for the PED mechanism, and recursive formulas for the state estimator are designed based on the principle of minimum mean squared error. Sufficient conditions are derived to guarantee the ultimate boundedness of the estimation error variance matrix. Finally, the proposed PED-based recursive state estimation scheme is evaluated through two simulation examples to demonstrate its effectiveness.