Issue |
Security and Safety
Volume 1, 2022
|
|
---|---|---|
Article Number | 2022005 | |
Number of page(s) | 16 | |
Section | Industrial Control | |
DOI | https://doi.org/10.1051/sands/2022005 | |
Published online | 22 July 2022 |
Research Article
Optimal injection attack strategy for cyber-physical systems: a dynamic feedback approach
School of Electronics and Information Engineering, Tongji University, Shanghai, 201804, China
* Corresponding author (email: zhang_hao@tongji.edu.cn)
Received:
30
December
2021
Revised:
21
February
2022
Accepted:
14
March
2022
This paper investigates the system security problem of cyber-physical systems (CPSs), which is not only more practical but also more significant to deal with than the detecting faults problem. The purpose of this paper is to find an optimal attack strategy that maximizes the output error of the attacked system with low energy consumption. Based on a general model of linear time-invariant systems and a key technical lemma, a new optimal attack strategy for the meticulously designed false data injection attack is constructed. It is worth mentioning that compared with the existing model-based attack strategies, the designed one is more general and the corresponding attack strategy is more easily implemented when system states and external input are inaccessible. Key to overcoming the inaccessible information, a dynamic observer in the form of Luenberger is constructed. Finally, a networked magnetic levitation steel ball movement system is applied to illustrate the effectiveness of the proposed scheme.
Key words: False data injection attack / Dynamic output feedback / Attack strategy design / Cyber-physical systems
Citation: Gao S, Zhang H, Wang ZP and et al. Optimal injection attack strategy for cyber-physical systems: a dynamic feedback approach. Security and Safety 2022; 1: 2022005. https://doi.org/10.1051/sands/2022005
© The Author(s) 2022. Published by EDP Sciences and China Science Publishing & Media Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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