Privacy‐Preserving Asymmetric Bipartite Consensus for Multi‐Agent Systems Under Cyber Attacks

ABSTRACT This paper addresses the privacy‐preserving and security control issues of multi‐agent systems (MASs) in cooperative‐competitive networks subject to multiple cyber attacks. Firstly, a unified attack model is developed to represent the simultaneous occurrence of Denial‐of‐Service (DoS) and False Data Injection (FDI) attacks in MASs. Secondly, considering the existence of privacy‐theft attacks, a sub‐state exchange (SSE) approach is introduced to protect the privacy of the agents' initial state from being stolen. Then, based on the Kalman filter, a state estimation‐based security protection mechanism is proposed under the joint attacks. The mechanism ensures that the agents use secure state values to achieve asymmetric bipartite consensus for MASs. Finally, simulation experiments are conducted to validate the effectiveness of the proposed methods.

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Publication Details

Journal
International Journal of Robust and Nonlinear Control
Published
2026-01-02
DOI
https://doi.org/10.1002/rnc.70307
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
0.00
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article

Privacy‐Preserving Asymmetric Bipartite Consensus for Multi‐Agent Systems Under Cyber Attacks

Hongyong Yang, Fan Tao Fang, Fei Liu, Li Liu
International Journal of Robust and Nonlinear Control
Smart Grid Security and Resilience
article

Privacy‐Preserving Asymmetric Bipartite Consensus for Multi‐Agent Systems Under Cyber Attacks

Hongyong Yang, Fan Tao Fang, Fei Liu, Li Liu
article en

Abstract

ABSTRACT This paper addresses the privacy‐preserving and security control issues of multi‐agent systems (MASs) in cooperative‐competitive networks subject to multiple cyber attacks. Firstly, a unified attack model is developed to represent the simultaneous occurrence of Denial‐of‐Service (DoS) and False Data Injection (FDI) attacks in MASs. Secondly, considering the existence of privacy‐theft attacks, a sub‐state exchange (SSE) approach is introduced to protect the privacy of the agents' initial state from being stolen. Then, based on the Kalman filter, a state estimation‐based security protection mechanism is proposed under the joint attacks. The mechanism ensures that the agents use secure state values to achieve asymmetric bipartite consensus for MASs. Finally, simulation experiments are conducted to validate the effectiveness of the proposed methods.

International Journal of Robust and Nonlinear Control
Ludong University (CN), Southeast University (BD)
Peace, Justice and strong institutions
Openalex Percentile: Top 98%
Smart Grid Security and Resilience
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