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基于辅助信息补偿和控制信号编码的重放攻击检测方法

张正道 杨佳佳 谢林柏

张正道, 杨佳佳, 谢林柏. 基于辅助信息补偿和控制信号编码的重放攻击检测方法. 自动化学报, 2021, x(x): 1−11 doi: 10.16383/j.aas.c210092
引用本文: 张正道, 杨佳佳, 谢林柏. 基于辅助信息补偿和控制信号编码的重放攻击检测方法. 自动化学报, 2021, x(x): 1−11 doi: 10.16383/j.aas.c210092
Zhang Zheng-Dao, Yang Jia-Jia, Xie Lin-Bo. Replay attack detection method based on auxiliary information compensation and control signal coding. Acta Automatica Sinica, 2021, x(x): 1−11 doi: 10.16383/j.aas.c210092
Citation: Zhang Zheng-Dao, Yang Jia-Jia, Xie Lin-Bo. Replay attack detection method based on auxiliary information compensation and control signal coding. Acta Automatica Sinica, 2021, x(x): 1−11 doi: 10.16383/j.aas.c210092

基于辅助信息补偿和控制信号编码的重放攻击检测方法

doi: 10.16383/j.aas.c210092
基金项目: 国家重点研发计划课题(2018YFB1701903)资助
详细信息
    作者简介:

    张正道:博士, 江南大学物联网工程学院副教授, 主要研究方向为信息物理系统安全性, 系统状态监测与故障诊断. 本文通信作者. Email: wxzzd@jiangnan.edu.cn

    杨佳佳:江南大学物联网工程学院硕士研究生. 主要研究方向为信息物理系统的攻击检测. Email: 6181905010@stu.jiangnan.edu.cn

    谢林柏:博士, 江南大学物联网工程学院教授. 主要研究方向为过程建模与控制, 智能检测与系统安全性等. Email: Xie_linbo@jiangnan.edu.cn

Replay Attack Detection Method Based on Auxiliary Information Compensation and Control Signal Coding

Funds: Supported by National Key Research and Development Program of China (No. 2018YFB1701903)
More Information
    Author Bio:

    ZHANG Zheng-Dao Ph.D., professor at the School of Internet of Things Engineering, Jiangnan University. His research interest covers security of cyber physics system, state monitoring and fault diagnosis. Corresponding author of this paper

    YANG Jia-Jia Master student at the School of Internet of Things Engineering, Jiangnan University. Her main interest is attack detection in cyber physical systems

    XIE Lin-Bo Ph.D., professor at the School of Internet of Things Engineering, Jiangnan University. His research interest covers process modeling and control, intelligent detection and system safety

  • 摘要: 在最优控制信号中加入编码信号是实现信息物理系统重放攻击检测的有效方法, 但会造成系统控制性能的损失. 如何在保证重放攻击检测率条件下降低系统的控制性能损失是一个值得研究的问题. 本文提出了一种基于辅助信息补偿的控制信号编码检测方法, 通过向测量值添加辅助信号补偿控制编码信号对最优状态估计的影响. 首先, 论文证明了此方案下重放攻击的可检测性, 导出了检测率的上界和检测函数阈值间的定量关系. 其次证明了加入辅助信号后系统控制信号与未添加编码信息时相同, 之前时刻的控制编码信号不会造成累积效应. 因此系统当前时刻的控制性能损失仅与当前时刻编码信号的大小有关. 最后, 将编码信号的协方差矩阵, 检测率和检测阈值之间的关系表示成一个最优化问题, 给出了编码信号方差的计算方法. 仿真结果表明, 本文方法能有效地检测重放攻击的发生, 且系统控制的性能损失较小.
  • 图  1  本文所提方法下的系统框图

    Fig.  1  System diagram under the scheme proposed in this paper

    图  2  直流电机系统正常运行下的检测函数曲线

    Fig.  2  The detection function curve of the normal DC motor system

    图  3  攻击场景1下的检测函数曲线

    Fig.  3  The detection function curve under attack scenario 1

    图  4  攻击场景2下的检测函数曲线

    Fig.  4  The detection function curve under attack scenario 2

    图  5  攻击场景3下的检测函数曲线

    Fig.  5  The detection function curve under attack scenario 3

    图  6  本文所提的方法和不同方法的性能损失函数曲线对比图

    Fig.  6  Comparison between the performance index of schemes in this paper and other papers

    表  1  噪声方差及性能指标比较

    Table  1  Comparison of noise variance and performance index of different schemes

    ADR${{\varSigma }_{\rm{u}}}$$J$
    本文方法75%0.435323.2778
    80%0.545029.1433
    文[17]方法75%0.761548.9837
    80%0.996464.0928
    文[18]方法71.02%1.001064.3244
    81.20%1.500096.4850
    文[15]方法75%2.7166174.7383
    80%3.4018218.8113
    下载: 导出CSV
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  • 收稿日期:  2021-01-28
  • 网络出版日期:  2021-07-06

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