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Secure multi-dimensional consensus algorithm against malicious attacks
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AI
DOI：10.1016/j.automatica.2023.111224.png)
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Abstract
En 中文
In this paper, we investigate the problem of multi-dimensional consensus subject to the internal agent dynamics constraint and external non-cooperative malicious attacks. We propose a secure discrete-time multi-dimensional consensus algorithm (SMCA), where two-hop information is utilized to check the integrity of neighboring agents' information. Furthermore, we derive a necessary and sufficient condition for all normal agents to achieve consensus exponentially under SMCA. For the boundary-case attacks under SMCA, we first cast the problem as an equivalent problem of multi-dimensional consensus with nonuniform time-delays, and then obtain the analytical expression of the attacks' effects on the final state and convergence rate. Compared with the existing works, SMCA can achieve multi-dimensional consensus for all normal agents with local dynamics even when the number of compromised agents is unknown. Finally, extensive simulations demonstrate the effectiveness of the proposed algorithm.& COPY; 2023 Published by Elsevier Ltd.
Keywords:
Multi-dimensional consensus
Malicious attacks
Secure algorithm
Two-hop information
Incremental norm
Journal
IF:
5.9
Papers:
1.2W
Citations:
5.2W