A Linear Matrix Inequality based Attack Detection Approach for Networked Control Systems
In networked control systems, the communication links and physical system components are coupled and hence vulnerable to a variety of attacks. Certain class of attacks on the communication network has a tendency to change the traffic flow causing delays and packet losses to increase, thus affecting the stability of the physical system. Therefore in this paper, a novel observer based flow control and detection scheme is proposed to capture the abnormality in traffic flow through the bottleneck node of the communication network by generating the attack detection residual. A linear matrix inequality (LMI) based controller design is proposed that ensures system stability by detecting attacks on the network as well as on the physical system. Since the dynamics of the physical system depend upon the network induced delay and packet losses, it is stabilized by adjusting the controller gains based on network state provided certain conditions are met. Simulation results are included to demonstrate the applicability of the proposed schemes against a class of attacks represented by attack models.
H. Niu et al., "A Linear Matrix Inequality based Attack Detection Approach for Networked Control Systems," Proceedings of the 2018 IEEE Conference on Decision and Control (2018, Miami Beach, FL), pp. 5470 - 5475, Institute of Electrical and Electronics Engineers (IEEE), Dec 2018.
The definitive version is available at https://doi.org/10.1109/CDC.2018.8619138
2018 IEEE Conference on Decision and Control, CDC 2018 (2018: Dec. 17-19, Miami Beach, FL)
Electrical and Computer Engineering
Intelligent Systems Center
Keywords and Phrases
Controllers; Linear matrix inequalities; Packet loss; System stability; Attack detection; Controller designs; Controller gain; Detecting attacks; Detection scheme; Network-induced delays; Observer-based; Physical systems; Networked control systems
International Standard Book Number (ISBN)
International Standard Serial Number (ISSN)
Article - Conference proceedings
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01 Dec 2018