Data-Driven Attack Detection and Identification for Cyber-Physical Systems Under Sparse Sensor Attacks: Iterative Reweighted l2/l1 Recovery Approach

This paper investigates the data-based attack detection and identification for cyber-physical systems (CPSs) under sparse sensor attacks. In order to improve the identification performance, a novel scheme based on an iterative reweighted <inline-formula> <tex-math notation="LaTeX"...

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Vydáno v:	IEEE transactions on circuits and systems. I, Regular papers Ročník 72; číslo 6; s. 2890 - 2902
Hlavní autoři:	Wang, Jun-Lan, Li, Xiao-Jian
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.06.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Accuracy Algorithms Attack detection and identification Cyber-physical systems cyber-physical systems (CPSs) data-driven Iterative algorithms iterative reweighted l₂/l₁ (IR-l₂/l₁) minimization algorithm Mathematical models Minimization Noise Noise measurement Norms Optimization Security sparse attacks Vectors
ISSN:	1549-8328, 1558-0806
On-line přístup:	Získat plný text
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