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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, 2022, 48(11): 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, 2022, 48(11): 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, 2022, 48(11): 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, 2022, 48(11): 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. 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.主要研究方向为智能电网攻击检测与防御. E-Mail: wangxinyuphd@163.com

    关新平:上海交通大学电子信息与电气工程学院教授. 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. E-mail: xpguan@sjtu.edu.cn

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

Funds: Supported by National Nutural Science Faudation of China (61873228)
More Information
    Author Bio:

    LUO Xiao-Yuan Professor at the School of Electrical Engineering, Yanshan University. He received his Ph.D. degree in control science and engineering from Yanshan University in 2005. His research interest covers detection of cyber attack of CPS and networked control systems

    PAN Xue-Yang  Master student in the Department of Control Science and Engineering, Yanshan University. His research interest covers Kalman filter and smart grid attack detection

    WANG Xin-Yu  Ph.D. canadate at the School of Electrical Engineering, Yanshan University. His research interest covers attack detection and defense in smart grid

    GUAN Xin-Ping Professor at the School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University. He received his Ph.D. degree in control science and engineering from Harbin Institute of Technology in 1999. His research interest covers wireless networked systems and detection of cyber attack in CPS

  • 摘要: 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 (Unscented Kalman filter, UKF) 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、巴氏系数检测方法进行比较. 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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出版历程
  • 收稿日期:  2019-09-06
  • 网络出版日期:  2022-10-25

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