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基于自适应Kalman滤波的智能电网假数据注入攻击检测

罗小元 潘雪扬 王新宇 关新平

罗小元, 潘雪扬, 王新宇, 关新平. 基于自适应Kalman滤波的智能电网假数据注入攻击检测. 自动化学报, 2020, 41(x): 1−12 doi: 10.16383/j.aas.c190636
引用本文: 罗小元, 潘雪扬, 王新宇, 关新平. 基于自适应Kalman滤波的智能电网假数据注入攻击检测. 自动化学报, 2020, 41(x): 1−12 doi: 10.16383/j.aas.c190636
Luo Xiao-Yuan, Pan Xue-Yang, Wang Xin-Yu, Guan Xin-Ping. Detection of False Data Injection Attack in Smart Grid via Adaptive Kalman Filtering . Acta Automatica Sinica, 2020, 41(x): 1−12 doi: 10.16383/j.aas.c190636
Citation: Luo Xiao-Yuan, Pan Xue-Yang, Wang Xin-Yu, Guan Xin-Ping. Detection of False Data Injection Attack in Smart Grid via Adaptive Kalman Filtering . Acta Automatica Sinica, 2020, 41(x): 1−12 doi: 10.16383/j.aas.c190636

基于自适应Kalman滤波的智能电网假数据注入攻击检测

doi: 10.16383/j.aas.c190636
基金项目: 国家自然科学基金(61873228)资助
详细信息
    作者简介:

    罗小元:燕山大学自动化系教授. 2005年获得燕山大学控制科学与工程学科博士学位 主要研究方向为网络控制系统, CPS网络攻击检测等. E-Mail: xyluo@ysu.edu.cn

    潘雪扬:燕山大学控制科学与工程专业硕士研究生. 主要研究方向为卡尔曼滤波和智能电网攻击检测. E-Mail: onty123@126.com

    王新宇:燕山大学控制科学与工程专业博士研究生.主要从事智能电网攻击检测与防御研究. E-Mail: wangxinyuphd@163.com

    关新平:上海交通大学自动化系教授. 1999年获得哈尔滨工业大学控制科学与工程学科博士学位.主要研究方向为无线网络系统, CPS网络攻击检测等. E-Mail: xpguan@sjtu.edu.cn

Detection of False Data Injection Attack in Smart Grid via Adaptive Kalman Filtering

  • 摘要: 本文研究了一种针对智能电网中假数据注入攻击的有效检测方法. 假数据注入攻击可以保持攻击前后残差基本不变, 绕过传统的不良数据检测技术. 首先基于电网模型, 分析了假数据注入攻击的攻击特性, 针对噪声统计特性未知且无迹Kalman滤波不稳定的现象, 提出了自适应平方根无迹Kalman滤波改进算法. 基于状态估计值, 结合中心极限定理提出检测算法, 并与欧几里得检测方法, 巴氏系数检测方法作比较. 最后, 仿真表明本文所提检测算法的优越性.
  • 图  1  3总线电网模型

    Fig.  1  3-bus grid model

    图  2  系统遭受攻击框图

    Fig.  2  block diagram of System under attack

    图  3  ASRUKF下的状态估计

    Fig.  3  State estimation in ASRUKF

    图  4  两种检测方法针对隐蔽假数据攻击

    Fig.  4  Two detection methods for covert false data attack

    图  5  巴氏相似性系数

    Fig.  5  Bhattacharyya coefficient

    图  6  $S\tilde x$的Q-Q图

    Fig.  6  quantile-quantile plot of $S\tilde x$

    图  7  本文提出的攻击检测方法

    Fig.  7  Attack detection proposed in this paper

    图  8  误检率${P_F}$

    Fig.  8  False alarm rate ${P_F}$

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