A novel adaptive cooperative attack design against cyber-physical systems via mixed H-infinity/H- index

Tian-Yu Zhang; Dan Ye; Tianyu Zhang

doi:10.1016/j.jfranklin.2018.09.028

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A novel adaptive cooperative attack design against cyber-physical systems via mixed H-infinity/H- index

Journal article

Peer reviewed

A novel adaptive cooperative attack design against cyber-physical systems via mixed H-infinity/H- index

Tian-Yu Zhang, Dan Ye and Tianyu Zhang

Journal of the Franklin Institute, Vol.358(1), pp.17-34

01/01/2021

DOI: 10.1016/j.jfranklin.2018.09.028

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Abstract

In this paper, a novel cooperative attack policy comprising adaptive and bias signals is studied against the cyber-physical systems (CPSs) based on the model knowledge. From the attacker's stand point, the design objective is deteriorating the system performance and deceiving the previously equipped detector in the CPSs. Combining with H-infinity and H- indexes, the bias signal is elaborately designed to compromise the systems by applying the linear matrix inequality (LMI) technology. Different from the existing works, in order to increase the attack effectiveness, an adaptive signal is also injected to compensate the possible external disturbance by the attacker. Moreover, some technology difficulties in the H-infinity/H- attack design problems are also investigated with the LMI approach. Finally, a practical example is given to illustrate the effectiveness and stealthiness of the cooperative attack policy. (C) 2018 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

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Details

Title: Subtitle: A novel adaptive cooperative attack design against cyber-physical systems via mixed H-infinity/H- index
Creators: Tian-Yu Zhang - Northeastern Univ, Coll Informat Sci & Engn, Shenyang, Liaoning, Peoples R China
Dan Ye - Northeastern University
Tianyu Zhang - Computer Science
Resource Type: Journal article
Publication Details: Journal of the Franklin Institute, Vol.358(1), pp.17-34
Publisher: Elsevier
DOI: 10.1016/j.jfranklin.2018.09.028
ISSN: 0016-0032
eISSN: 1879-2693
Number of pages: 18
Grant note: N160402004 / Fundamental Research Funds for the Central Universities 61773097 / National Natural Science Foundation of China; National Natural Science Foundation of China (NSFC) 201517 / Liaoning BaiQianWan Talents Program
Language: English
Date published: 01/01/2021
Academic Unit: Computer Science
Record Identifier: 9984696578202771

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