文献类型：期刊文献

英文题名：Distributed Secure State Estimation Against Stealthy Attacks

作者：Yu, Yan[1];Yang, Wen[1];Yuan, Hongbo[1];Li, Longyu[1];Yang, Chao[1]

机构：[1]East China Univ Sci & Technol, Key Lab Smart Mfg Energy Chem Proc, Shanghai 200237, Peoples R China

年份：2025

卷号：32

起止页码：1930

外文期刊名：IEEE SIGNAL PROCESSING LETTERS

收录：;EI(收录号：20251818357928);WOS:【SCI-EXPANDED(收录号:WOS:001487988600009)】；

基金：This work was supported in part by the National Key R&D Program of China under Grant 2023YFF1204805, and in part by the National Natural Science Foundation of China under Grant 62336005. The associate editor coordinating the review of this article and approving it for publication was Prof. Zhongyun Hua.

语种：英文

外文关键词：Detectors; Encryption; Encoding; Image edge detection; Distributed databases; Nickel; State estimation; Data communication; Training; Protection; stealthy attack; encryption

摘要：This paper investigates the issue of False Data Injection (FDI) attacks within distributed state estimation. In the network, each sensor transmits its state estimate to neighboring nodes. Based on the detection variables inherent to distributed systems, we construct a covert attack strategy to bypass data detectors and degrade the estimation performance of the system. Furthermore, we propose an enhanced stealthy attack strategy, which aims to prevent interference from the attacks of neighboring edges that otherwise counteract against each other. To improve the detection rate of attacks, a detector with a dynamic coding strategy is designed to secure data transmission. The destructiveness of the stealthy attacks and the effectiveness of the detection mechanism are demonstrated through numerical examples.