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Geometry-Based Data-Driven Complete Stealthy Attacks Against Cyber-Physical Systems

delete2024-11-01
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PRE
AI
K
Kaiyu Wang
叶
叶丹 (Dan Ye) *
DOI:10.1109/TNSE.2024.3458095delete
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摘要

摘要

En 中文
This paper proposes a data-driven complete stealthy attack strategy against cyber-physical systems (CPSs) based on the geometric approach. The attacker aims to degrade estimation performance and maintain stealthiness by compromising partial communication links of the actuator and sensor. Different from the classic analysis methods that require accurate model parameters, we focus on how to establish the connection between geometry and data-driven approaches to represent the malicious behavior of attacks on state estimation. First of all, the existence of complete stealthy attacks is analyzed. Then, the maximal attached stealthy subspace and the set of estimation errors under complete stealthy attacks are analyzed intuitively from the geometric point of view. On this basis, the complete stealthy subspace is constructed with the subspace identification method, which is applied to generate the corresponding stealthy attack sequence through the collected system input-output data. Finally, simulation results are provided to illustrate the effectiveness of the proposed strategies.
Keyword:
State estimation
Vectors
Geometry
Detectors
Actuators
Estimation error
Simulation
Cyber-physical systems (CPSs)
complete stealthy
data-driven
false data injection attack
geometry

期刊

I
IEEE Transactions on Network Science and Engineering
IF:
7.9
论文数:
2.6K
被引数:
10.0K

机构

N
northeastern university - china
学者数:
3.2W
论文数: 2.7W
被引数: 37
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