A Novel Attack Detection for Linear Systems With Unknown-But-Bounded Noises

被引：12

作者：

Liu, Hao ^{[1
]}

Wang, Shaodong ^{[1
]}

Niu, Ben ^{[2
]}

Li, Yuzhe ^{[3
]}

机构：

[1] Shenyang Aerosp Univ, Sch Automat, Shenyang 110136, Peoples R China

[2] Shandong Normal Univ, Sch Informat Sci & Engn, Jinan 250014, Peoples R China

[3] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110004, Peoples R China

来源：

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | 2022年 / 52卷 / 07期

基金：

中国国家自然科学基金;

关键词：

Symmetric matrices; State estimation; System performance; Stochastic processes; Security; Optimization; Noise measurement; Linear parameter-varying (LPV) systems; state estimation; unknown-but-bounded (UBB) noises; GUARANTEED STATE ESTIMATION; ZONOTOPES;

D O I：

10.1109/TSMC.2021.3090150

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 article proposes a novel attack detection approach based on zonotopes for linear parameter-varying (LPV) systems with unknown-but-bounded (UBB) noises. The following three types of attacks are considered: 1) denial-of-service (DoS) attacks; 2) replay attacks (RAs); and 3) false-data-injection (FDI) attacks. In order to reduce the conservativeness, a free-weighting matrix is introduced, which can be computed by solving an optimization problem. Moreover, the radius of the intersection zonotope can be guaranteed to be limited as well. Furthermore, it is not necessary to acquire the knowledge about the specific type of attack in advance. Finally, a numerical example is given to illustrate the validity of the given method.

引用

页码：4223 / 4232

页数：10

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