中国电机工程学报2025，Vol.45Issue(19)：7468-7480,中插17,14.DOI:10.13334/j.0258-8013.pcsee.240744
基于自适应差分进化-模糊宽度学习系统的FDIA定位检测方法
FDIA Localization Method Based on Adaptive Differential Evolution and Fuzzy Broad Learning System
摘要
Abstract
As a key component of the energy internet,cyber-physical power systems face the threat of false data injection attacks.Detection techniques for such attacks often neglect the localization of the attack injection,and research attempting to solve this problem has difficulty balancing detection accuracy and computation time.Therefore,this paper proposes a false data injection attack localization method based on adaptive differential evolution-fuzzy broad learning system.The proposed algorithm employs a fuzzy broad learning system with a transversal network structure to constitute the localization algorithm,which realizes the fast detection.Meanwhile,an adaptive differential evolution algorithm is proposed to perform feature selection on the measured data and eliminate the redundant features,which effectively improves the accuracy of the algorithm for location detection.Extensive simulations in IEEE-14 and 57-node systems verify that the proposed method is capable of precise localization of spurious data injection attacks,and has better accuracy,precision,recall,and F1-score compared with multiple traditional detection algorithms.关键词
能源互联网/电力信息物理系统/虚假数据注入攻击/模糊宽度学习系统/差分进化Key words
energy internet/cyber-physical power systems/false data injection attack/fuzzy broad learning system/differential evolution分类
信息技术与安全科学引用本文复制引用
席磊,陈洪军,彭典名,王文卓,白芳岩..基于自适应差分进化-模糊宽度学习系统的FDIA定位检测方法[J].中国电机工程学报,2025,45(19):7468-7480,中插17,14.基金项目
国家自然科学基金项目(52277108,52477104) （52277108,52477104）
宜昌市自然科学研究项目(A23-2-001).Project Supported by National Natural Science Foundation of China(52277108,52477104) （A23-2-001）
Yichang Municipal Natural Science Foundation(A23-2-001). （A23-2-001）
