Privacy-preserving resilient bipartite consensus of multi-agent systems: A differential privacy scheme

IF 3.7 2区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Ran Tian, Jie Mei, Guangfu Ma
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引用次数: 0

Abstract

This paper addresses the issue of differential privacy-preserving in multi-agent systems (MASs) with the existence of misbehaving agents and antagonistic interactions over a signed digraph. Even with the existence of a maximum of f faulty agents within the network, non-faulty agents pursue resilient bipartite consensus, with the requirement that their initial conditions can fulfill differential privacy. To this end, we propose the differentially private absolute weighted mean subsequence reduced (DP-AW-MSR) algorithm. Under the structurally balanced signed digraph with sufficient connectivity in terms of robustness, three essential properties of this algorithm are characterized: resilient bipartite consensus, accuracy and differential privacy. Numerical simulation is given to illustrate the effectiveness of our findings.
多智能体系统的隐私保护弹性二部共识:一种差分隐私方案
本文讨论了多智能体系统(MASs)中存在行为不端的智能体和在有向图上的对抗交互的微分隐私保护问题。即使网络中存在最多f个故障代理,无故障代理也会追求弹性二部共识,要求其初始条件能够满足差分隐私。为此,我们提出了差分私有绝对加权平均子序列缩减(DP-AW-MSR)算法。在鲁棒性方面具有足够连通性的结构平衡签名有向图下,该算法具有弹性二部一致性、准确性和差分隐私性三个基本特性。数值模拟结果说明了本文研究结果的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Nonlinear Analysis-Hybrid Systems
Nonlinear Analysis-Hybrid Systems AUTOMATION & CONTROL SYSTEMS-MATHEMATICS, APPLIED
CiteScore
8.30
自引率
9.50%
发文量
65
审稿时长
>12 weeks
期刊介绍: Nonlinear Analysis: Hybrid Systems welcomes all important research and expository papers in any discipline. Papers that are principally concerned with the theory of hybrid systems should contain significant results indicating relevant applications. Papers that emphasize applications should consist of important real world models and illuminating techniques. Papers that interrelate various aspects of hybrid systems will be most welcome.
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