A Median-based Resilient Distributed Optimization Algorithm Against Byzantine Attack

Author:

Xu Chentao1,Liu Qingshan23ORCID

Affiliation:

1. School of Cyber Science and Engineering, Southeast University, Nanjing 210096, China

2. School of Mathematics, Frontiers Science Center for Mobile Information Communication and Security, Southeast University, Nanjing 210096, China

3. Purple Mountain Laboratories, Nanjing 211111, China

Abstract

Distributed optimization algorithms are widely used for solving science and engineering problems in recent years. However, these algorithms become vulnerable in the face of external attacks, so it is urgent to develop novel resilient distributed optimization algorithms against attacks. In this paper, we design a novel median-based resilient distributed optimization algorithm to defend the Byzantine attack. The existence of transition matrix is proved, and the convergence and optimality of the proposed algorithm are analyzed. Simulation experiments are performed to verify the effectiveness of the proposed algorithm and the results show that it is more effective than the compared one and can get the best possible results against the attack.

Publisher

World Scientific Pub Co Pte Ltd

Subject

Artificial Intelligence,Artificial Intelligence

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An Accelerated Gradient Tracking Algorithm with Projection Error for Distributed Optimization;2023 15th International Conference on Advanced Computational Intelligence (ICACI);2023-05-06

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