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Byzantine-Resilient Multiagent Distributed Optimization Under Redundancy
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DOI：10.1109/TCNS.2025.3583622.png)
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Abstract
En 中文
This article investigates the distributed multiagent resilient optimization problem under <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$f$</tex-math></inline-formula>-total Byzantine attacks, i.e., at most <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$f$</tex-math></inline-formula> agents transmitting different false information to different out-neighbors in the system. Compared with the previous research on Byzantine-resilient multiagent optimization problems, we do not impose the requirement of a fully connected communication topology. Under the redundancy of cost functions, we propose the distributed comparative gradient elimination resilient optimization algorithm based on the traditional assumptions on strongly convex global costs and Lipschitz continuous gradients. Under this algorithm, we address the limitation of previous relevant research, which only ensures that the estimates converge to a neighborhood of the optimal solution. We successfully prove that the local estimates of normal agents will converge to the optimal solution if the number of neighbors of normal agents is greater than a certain constant. Finally, a numerical experiment is provided to verify the correctness of the obtained results.
Keywords:
Byzantine attack
cost redundancy
cybersecurity
distributed optimization
multiagent system (MAS)
Journal
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5
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1.6K
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