基于自适应卡尔曼滤波器的智能电网隐蔽假数据攻击检测

Adaptive Kalman Filter-based Detection of Covert False Data Injection Attacks in Smart Grids

基于自适应卡尔曼滤波器研究了智能电网假数据注入攻击检测问题.首先通过给出电网的状态空间模型,对两种攻击进行描述:随机攻击和假数据注入攻击.其次,研究表明常用的卡方检测器可以有效检测随机攻击,但无法检测出隐蔽假数据注入攻击.由此进一步在分析假数据注入攻击隐蔽性的基础上,考虑实际噪声变化的影响,提出基于R,Q自适应动态估计的卡尔曼滤波器的方法检测此类攻击,给出其设计过程,并对隐蔽假数据注入攻击提出了检测判断方法.最后进行Matlab仿真实验,验证了提出的隐蔽假数据注入攻击检测方法的有效性.

The detection problem of covert false data injection attack（ FDIA） for smart grids by using adaptive Kalman filter（ AKF） is herein presented. The state-space model of the smart grid is employed to study the characteristics of the random attack and the FDIA. However, an accurate analysis revealed that the commonly used χ^2-detector could only detect random attack efficiently,but not the FDIA. To overcome this drawback,the AKF is applied to assess FDIA by analyzing the covert characteristics of the FDIA and the change of actual noise. Finally,the simulation experiments verify the effectiveness of the proposed FDIA detection method.