中国电机工程学报2025，Vol.45Issue(18)：7110-7122,中插8,14.DOI:10.13334/j.0258-8013.pcsee.240412
数据驱动算法的电力信息物理系统FDIA定位检测
FDIA Location Detection for Data-driven Algorithms in Cyber-physical Power Systems
摘要
Abstract
False data injection attacks(FDIA)seriously threaten the security of cyber-physical power systems(CPPS).For the problem that the traditional detection methods are unable to identify attacks accurately and locate the attacked buses quickly,a FDIA localization method is proposed based on data-driven algorithms in CPPS.Firstly,the kernel extreme learning machine is combined with the autoencoder to form a multi-layer kernel extreme learning machine,which learns the power measurement data layer by layer.Then,the Harris hawk optimization,which incorporates the tent mapping and golden sine strategy,is utilized to optimize the parameters of the multi-layer kernel extreme learning machine,in order to improve the optimization speed and convergence accuracy.Finally,the proposed algorithm is verified by simulation in IEEE-14 and IEEE-118 bus test systems.The results show that the proposed algorithm has better detection speed,accuracy,precision,recall,and F1-Sorce compared to other algorithms,and can locate the attacked buses quickly and accurately.关键词
虚假数据注入攻击/电力信息物理系统/定位检测/哈里斯鹰优化算法/核极限学习机Key words
false data injection attacks/cyber-physical power systems/location detection/Harris hawk optimization/kernel extreme learning machine分类
信息技术与安全科学引用本文复制引用
席磊,彭典名,曹伟,陈洪军,白芳岩,王文卓..数据驱动算法的电力信息物理系统FDIA定位检测[J].中国电机工程学报,2025,45(18):7110-7122,中插8,14.基金项目
国家自然科学基金项目(52277108) （52277108）
湖北省高等学校优秀中青年科技创新团队计划项目(T2020006).Project Supported by National Natural Science Foundation of China(52277108) （T2020006）
Excellent Young and Middle-aged Science and Technology Innovation Team Project of Hubei Universities(T2020006). （T2020006）
