王新宇,王相杰,张明月,程朋飞,王书征
WANG Xinyu,WANG Xiangjie,ZHANG Mingyue,CHENG Pengfei,WANG Shuzheng

• 1:燕山大学
• 2:江苏省配电网智能技术与装备协同创新中心
• 3:徐州工程学院

摘要(Abstract)：

作为典型的信息物理攻击，虚假数据可以实现测量输出无变化，从而欺骗基于卡方检测器的检测。为此，提出一种基于改进自适应免疫遗传算法的智能电网虚假数据攻击检测方法。首先，建立三相电压测量电网模型，分析虚假数据攻击的隐蔽特性。然后，利用抗体之间的相似度指数建立异常数据检测器，对入侵的虚假数据进行检测。此外，通过引入选择、交叉、变异算子的自适应设计，提高免疫遗传算法的收敛速度和全局寻优能力，从而改善攻击检测的性能指标。最后，通过仿真实验分析所提检测方法对虚假数据攻击的检测率和误检率，结果验证了该方法的有效性。
As a typical cyber-physical attack, false data are measured unchanged, thus deceiving the detection based on chi-square detector. To this end, a false data attack detection method for smart grid based on an improved adaptive immune genetic algorithm(AIGA) is proposed. First, a three-phase voltage measurement network model is established to analyze the hidden characteristics of the false data attack. Then, the similarity index between antibodies is utilized to establish an anomalous data detector to detect the intruding false data. In addition, the convergence speed and global optimization ability of the algorithm are improved by introducing the adaptive design of selection operators, crossover operators, and mutation operators, which improves the performance index of the attack detection. Finally, the detection rate and false detection rate of the proposed method for false data attack detection are analyzed through simulation experiments, and the results verify the effectiveness of the method.

关键词(KeyWords)： 智能电网;虚假数据攻击;改进自适应免疫遗传算法
smart grid;false data attack;improved AIGA

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金青年项目（62103357）;; 河北省自然科学基金青年项目（F2021203043）;; 河北省教育厅自然科学基金青年项目（QN2021139）;; 江苏省配电网智能技术与装备协同创新中心开放基金项目（XTCX202203）

作者(Author): 王新宇,王相杰,张明月,程朋飞,王书征
WANG Xinyu,WANG Xiangjie,ZHANG Mingyue,CHENG Pengfei,WANG Shuzheng

DOI: 10.19585/j.zjdl.202310010

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