Fast state estimation under sensor attacks: A sensor categorization approach

被引:9
作者
An, Liwei [1 ]
Yang, Guang-Hong [1 ,2 ]
机构
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Peoples R China
[2] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Cyber-physical systems; State estimation; Sensor attacks; Equivalence class; CYBER-PHYSICAL SYSTEMS;
D O I
10.1016/j.automatica.2022.110395
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In a sensor network, some sensors usually provide the same or equivalent measurement information, which is not taken into account by the existing secure state estimation methods against sparse sensor attacks such that the computational efficiency of these methods needs to be further improved. In this paper, by considering the observation equivalence of sensor measurement, a concept of analytic sensor types is introduced based on the equivalence class to develop a fast state estimation algorithm. By verifying the similarity degree of measurement data of a sensor type, the attack location information can be extracted to exclude some mismatching search candidates, without loss of estimation correctness. This confirms high speed performance of the proposed algorithm, since the number of sensor types is usually far less than the number of sensors. (C) 2022 Elsevier Ltd. All rights reserved.
引用
收藏
页数:9
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