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虚假数据注入攻击下多机器人系统协同寻源

王彪新 伍益明 郑宁 徐明

王彪新, 伍益明, 郑宁, 徐明. 虚假数据注入攻击下多机器人系统协同寻源. 自动化学报, 2024, 50(2): 1−14 doi: 10.16383/j.aas.c230252
引用本文: 王彪新, 伍益明, 郑宁, 徐明. 虚假数据注入攻击下多机器人系统协同寻源. 自动化学报, 2024, 50(2): 1−14 doi: 10.16383/j.aas.c230252
Wang Biao-Xin, Wu Yi-Ming, Zheng Ning, Xu Ming. Multi-robot system cooperative source seeking under false data injection attack. Acta Automatica Sinica, 2024, 50(2): 1−14 doi: 10.16383/j.aas.c230252
Citation: Wang Biao-Xin, Wu Yi-Ming, Zheng Ning, Xu Ming. Multi-robot system cooperative source seeking under false data injection attack. Acta Automatica Sinica, 2024, 50(2): 1−14 doi: 10.16383/j.aas.c230252

虚假数据注入攻击下多机器人系统协同寻源

doi: 10.16383/j.aas.c230252
基金项目: 国家自然科学基金(62073109), 浙江省公益技术应用研究(LGF21F020011)资助
详细信息
    作者简介:

    王彪新:杭州电子科技大学网络空间安全学院硕士研究生. 主要研究方向为多机器人系统网络安全, 寻源问题. E-mail: 211270007@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. 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. 本文通信作者. E-mail: ymwu@hdu.edu.cn

    郑宁:杭州电子科技大学网络空间安全学院研究员. 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

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

Multi-robot System Cooperative Source Seeking Under False Data Injection Attack

Funds: Supported by National Natural Science Foundation of China (62073109) and Zhejiang Provincial Public Welfare Research Project of China (LGF21F020011)
More Information
    Author Bio:

    WANG Biao-Xin Master student at the School of Cyberspace, Hangzhou Dianzi University. His research interest covers cyber security for multi-robot system and source seeking

    WU Yi-Ming Associate professor at the School of Cyberspace, Hangzhou Dianzi University. His research interest covers distributed system secure control and cyber security for multi-agent system. Corresponding author of this paper

    ZHENG Ning Researcher at the School of Cyberspace, Hangzhou Dianzi University. His research interest covers information security, information management system, and multi-agent system

    XU Ming Professor at the School of Cyberspace, Hangzhou Dianzi University. His research interest covers network information security and digital forensics

  • 摘要: 聚焦多机器人系统协同寻源问题, 即通过驱使多个机器人相互协同寻找未知环境中物理信号放射源的位置. 由于执行任务的机器人通常处于户外开放网络环境中, 攻击者在网络中生成的虚假数据注入攻击容易导致多机器人系统寻源任务的失败. 为在网络攻击情形下仍旧能够追寻到源点, 提出一种基于弹性向量趋同的多机器人系统协同多维寻源方法. 有别于现有文献在处理多维寻源时将向量分解成各个维度上的标量进而设计基于标量的弹性趋同协议, 所提出的多维寻源方法不仅能够有效抵御虚假数据注入攻击完成寻源任务, 而且其界定的安全区间相较于传统基于标量信息界定的安全区间更加严格和精准. 在假设f-局部有界(f-locally bounded) 虚假数据注入攻击模型下, 理论分析给出正常机器人在所设计的控制协议下追寻到源点的充分必要条件. 仿真结果表明, 该方法在分布式多机器人系统协作寻源和抵抗恶意攻击方面具有优越性.
  • 图  1  弹性标量协议所界定的安全区间 (浅色方形区域) 和弹性向量协议所界定的安全区间 (深色区域)[17]

    Fig.  1  The security intervals defined by the resilient scalar protocol (Light square area) and the resilient vector protocol (Dark area)[17]

    图  2  环境中的机器人节点之间的通信关系和安全区域

    Fig.  2  The communication relationship and safe area among the robot nodes in the environment

    图  3  6个信息量的子集凸包和安全区域

    Fig.  3  The subset convex hull and safe area of six information value

    图  4  节点之间的通信(有向图)

    Fig.  4  Communication between nodes (Directed graph)

    图  5  $ t = 35$时使用弹性向量协同寻源方法的寻源轨迹

    Fig.  5  The source seeking trajectories of resilient vector cooperative source seeking at $ t = 35$

    图  6  $t$ = 10和$t$ = 20时$v_3$计算的安全区域和正常节点真实坐标并上源点位置的凸包

    Fig.  6  The safe area calculated by $v_3$ and the convex hull area of the real coordinates of the normal nodes with the source point position at $t = 10$ and $t = 20$

    图  7  正常节点真实坐标并上源点位置的凸包面积随迭代步时$t$的变化关系

    Fig.  7  The relation between the convex hull area of the real coordinates of the normal nodes with the source point position and the number of iteration $t $

    图  8  距离源点最远的节点与源点之间的距离随迭代步时$t$的变化关系

    Fig.  8  Relationship between the number of iteration $t$ and the distance between the source point and the node farthest from the source point

    图  9  未采用计算安全区域方法的寻源轨迹

    Fig.  9  The source seeking trajectories without calculation of safe area method

    图  10  基于弹性标量协议和基于本文所提方法的安全区间面积随迭代步时$ t$变化关系

    Fig.  10  The relationship between the number of iteration $t $ and the area of the safe interval based on the resilient scalar protocol and the method proposed in this paper

    图  11  添加干扰情况下的寻源轨迹

    Fig.  11  The source seeking trajectories with disturbance

    图  12  $t$ = 35时基于PSO&MSR的寻源轨迹[15]

    Fig.  12  The source seeking trajectories based on PSO&MSR[15] at $t = 35$

    图  13  当机器人节点初始位置在源点同一侧的情况下使用本文方法在$t$ = 30和$t$ = 45时的寻源轨迹

    Fig.  13  The source seeking trajectories based on the proposed method when the initial positions of the robot nodes are on the same side as the source point at $t $ = 30 and $t $ = 45

    图  14  当机器人节点初始位置在源点同一侧的情况下使用基于PSO&MSR的方法在 $t$ = 30和$t$ = 45时的寻源轨迹

    Fig.  14  The source seeking trajectories based on PSO&MSR when the initial positions of the robot nodes are on the same side as the source point at $t $ = 30 and $t $ = 45

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出版历程
  • 收稿日期:  2023-05-04
  • 录用日期:  2023-08-29
  • 网络出版日期:  2023-11-21

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