欺骗攻击下具备隐私保护的多智能体系统均值趋同控制

应晨铎; 伍益明; 徐明; 郑宁; 何熊熊

doi:10.16383/j.aas.c210889

欺骗攻击下具备隐私保护的多智能体系统均值趋同控制

doi: 10.16383/j.aas.c210889

应晨铎^1,,
伍益明^1,,
徐明^1,,
郑宁^1,,
何熊熊^2,

1.
杭州电子科技大学网络空间安全学院杭州 310018
2.
浙江工业大学信息工程学院杭州 310023

基金项目: 国家自然科学基金(61803135, 61873239, 62073109), 浙江省公益技术应用研究项目(LGF21F020011)资助

详细信息

作者简介:
应晨铎：杭州电子科技大学网络空间安全学院硕士研究生. 2020年获得浙大宁波理工学院软件工程学士学位. 主要研究方向为弹性趋同, 隐私保护和分布式系统安全. E-mail: cdying@hdu.edu.cn

伍益明：杭州电子科技大学网络空间安全学院副教授. 2016年获得浙江工业大学控制科学与工程博士学位. 主要研究方向为分布式系统安全控制, 多智能体系统网络安全和迭代学习控制. 本文通信作者. E-mail: ymwu@hdu.edu.cn

徐明：杭州电子科技大学网络空间安全学院教授. 2004年获得浙江大学博士学位. 主要研究方向为网络信息安全, 数字取证. E-mail: mxu@hdu.edu.cn

郑宁：杭州电子科技大学网络空间安全学院研究员. 1987年获得浙江大学硕士学位. 主要研究方向为信息安全, 信息管理系统和多智能体系统. E-mail: nzheng@hdu.edu.cn

何熊熊：浙江工业大学信息工程学院教授. 1997年获得浙江大学博士学位. 主要研究方向为迭代学习控制, 智能控制及其在多智能体系统和传感器网络中的应用. E-mail: hxx@zjut.edu.cn

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出版历程
- 收稿日期: 2021-09-15
- 录用日期: 2022-04-28
- 网络出版日期: 2022-05-19
- 刊出日期: 2023-02-20

Privacy-preserving Average Consensus Control forMulti-agent Systems Under Deception Attacks

1.
School of Cyberspace, Hangzhou Dianzi University, Hangzhou 310018
2.
College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023

Funds: Supported by National Natural Science Foundation of China (61803135, 61873239, 62073109) and Zhejiang Provincial Public Welfare Research Project of China (LGF21F020011)

More Information

Author Bio:
YING Chen-Duo　Master student at the School of Cyberspace, Hangzhou Dianzi University. He received his bachelor degree in software engineering from NingboTech University in 2020. His research interest covers resilient consensus, privacy preservation, and distributed system security

WU Yi-Ming　Associate professor at the School of Cyberspace, Hangzhou Dianzi University. He received his Ph.D. degree in control science and engineering from Zhejiang University of Technology in 2016. His research interest covers distributed system secure control, cyber-security for multi-agent systems, and iterative learning control. Corresponding author of this paper

XU Ming　Professor at the School of Cyberspace, Hangzhou Dianzi University. He received his Ph.D. degree from Zhejiang University in 2004. His research interest covers network security and digital forensics

ZHENG Ning　Professor at the Sc-hool of Cyberspace, Hangzhou Dianzi University. He received his master degree from Zhejiang University in 1987. His research interest covers information security, information management system, and multi-agent systems

HE Xiong-Xiong Professor at the College of Information Engineering, Zhejiang University of Technology. He received his Ph.D. degree from Zhejiang University in 1997. His research inter-est covers iterative learning control, intelligent control and its applications in multi-agent systems and sensor networks

摘要

摘要: 针对通信网络遭受欺骗攻击的离散时间多智能体系统, 研究其均值趋同和隐私保护问题. 首先, 考虑链路信道存在窃听者的情形, 提出一种基于状态分解思想的分布式网络节点值重构方法, 以阻止系统初始信息的泄露. 其次, 针对所构建的欺骗攻击模型, 利用重构后节点状态信息并结合现有的安全接受广播算法, 提出一种适用于无向通信网络的多智能体系统均值趋同控制方法. 理论分析表明, 该方法能够有效保护节点初始状态信息的隐私, 并能消除链路中欺骗攻击的影响, 实现分布式系统中所有节点以初始值均值趋同. 最后, 通过数值仿真实验验证了该方法的有效性.
- 多智能体系统 /
- 均值趋同 /
- 欺骗攻击 /
- 隐私保护 /
- 网络安全
Abstract: This paper investigates the average consensus and privacy-preserving problem for discrete-time multi-agent systems with deception attacks. First, considering the situation where there are eavesdroppers on the link channel, a distributed node value reconstruction method based on the idea of state decomposition is proposed to prevent the leakage of the initial information of the system. Then, under the constructed deception attack model, a novel average consensus control method for multi-agent systems with undirected communication networks is proposed, which uses the reconstructed node status information and combines with the secure acceptance and broadcast algorithm. Theoretical analysis shows that the proposed method can effectively protect the privacy of the initial state information of the nodes, and eliminate the influence of deception attacks in the links, and reach a consensus. Finally, numerical simulation experiments verify the effectiveness of the proposed method.
- Multi-agent systems /
- average consensus /
- deception attack /
- privacy-preserving /
- cyber security

HTML全文

图 1 状态分解方法示例图

Fig. 1 Example diagram of state decomposition method

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图 2 欺骗攻击下多智能体系统分布式网络示意图

Fig. 2 The diagram of the multi-agent system distributed network under deception attacks

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图 3 6个节点组成的多智能体系统通信拓扑图

Fig. 3 Network topology of multi-agent system with 6 nodes

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图 4 系统不满足强(2f + 1)-链路鲁棒图下各节点的状态量测值变化轨迹

Fig. 4 State trajectory of each node with system that does not meet the strong (2f + 1)-links robustness

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图 5 系统外部通信链路遭受欺骗攻击下各节点的状态量测值变化轨迹

Fig. 5 State trajectory of each node under deception attack on the external communication link of the system

下载: 全尺寸图片幻灯片

图 6 节点$ v_4 $内部遭受欺骗攻击的通信拓扑及攻击示意图

Fig. 6 Communication topology and attack diagram of the deception attack inside node $ v_4 $

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图 7 系统内部通信链路遭受欺骗攻击下使用状态分解算法各节点的状态量测值变化轨迹

Fig. 7 State trajectory of each node under deceptionattack on the internal communication link of thesystem by using the statedecomposition algorithm

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图 8 系统内部通信链路遭受欺骗攻击下使用本文算法各节点的状态量测值变化轨迹

Fig. 8 State trajectory of each node under deception attack on the internal communication link of the system by using the proposed algorithm

下载: 全尺寸图片幻灯片

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