Privacy-Preserving Adaptive Resilient Consensus for Multiagent Systems Under Cyberattacks

This article investigates the secure and privacy-preserving consensus problem of multiagent systems (MASs) with directed interaction topologies under multiple cyberattacks, which contain deception attacks and DoS attacks. First, a unified attack model is introduced to characterize such a multiple at...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on industrial informatics 2024-02, Vol.20 (2), p.1630-1640
Main Authors: Ying, Chenduo, Zheng, Ning, Wu, Yiming, Xu, Ming, Zhang, Wen-An
Format: Article
Language:English
Subjects:
Adaptation models
Adaptive algorithms
Algorithms
Consensus algorithm
Cyberattack
Cyberattacks
Denial of service attacks
directed graph
Informatics
Mathematical models
Multi-agent systems
Multiagent systems
multiagent systems (MASs)
Privacy
privacy preservation
resilient consensus
Robustness
Robustness (mathematics)
Synchronization
Topology
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This article investigates the secure and privacy-preserving consensus problem of multiagent systems (MASs) with directed interaction topologies under multiple cyberattacks, which contain deception attacks and DoS attacks. First, a unified attack model is introduced to characterize such a multiple attack phenomenon. Besides, considering the existence of eavesdroppers who can intercept the data transmitted on the links, a fully distributed agent value reconstruction method based on the idea of state decomposition is designed to prevent the leakage of the agent's initial information. Then, a novel privacy-preserving adaptive resilient consensus algorithm (PPARCA) with certain graph robustness condition for MASs under the multiple cyberattacks is proposed. The algorithm adaptively takes different countermeasures in the face of different cyberattacks. PPARCA uses the reconstructed agents' states and combines with the modified secure acceptance and broadcast algorithm (SABA). Theoretical analysis shows that the proposed algorithm can effectively protect the privacy of the initial state of the agents, and reach resilient consensus in the face of cyberattacks. Finally, numerical simulations and Raspberry Pi MASs practical application experiments demonstrate the effectiveness of the proposed results.
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2023.3280318