文献类型：期刊文献

中文题名：基于水印的参数不确定性电力系统攻击检测方法

英文题名：Watermarking-Based Attack Detection Method for Power System with Parameter Uncertainty

作者：陈佳玲[1];杨文[1]

机构：[1]华东理工大学能源化工过程智能制造教育部重点实验室,上海200237

年份：2025

卷号：51

期号：5

起止页码：671

中文期刊名：华东理工大学学报(自然科学版)

外文期刊名：Journal of East China University of Science and Technology

收录：;北大核心:【北大核心2023】；

语种：中文

中文关键词：状态估计;攻击检测;卡尔曼滤波;协同估计;网络化

外文关键词：state estimation;attack detection;Kalman filter;cooperative estimation;networking

摘要：针对具有参数不确定性的负载频率控制(LFC)系统中虚假数据注入(FDI)攻击检测问题,基于卡尔曼滤波法构建了LFC系统的状态估计模型。为了提高现有χ^(2)检测器的检测率,考虑了一种添加伪随机数水印矩阵的数据传输策略。与传统方法相比,在没有攻击的情况下,该策略不会增加计算复杂度或牺牲估计性能,以保障电力系统在复杂环境下可靠运行。此外,考虑到LFC系统存在参数不确定性问题,采用了粒子群优化(PSO)算法进行参数辨识,以提高估计模型与实际系统的匹配度。最后,提出一种基于伪随机数水印和PSO算法相结合的在线辨识-检测方法,并运用二区域LFC系统开展仿真实验,证实了上述方法的可行性与有效性。
A novel online identification and detection method based on watermarking and particle swarm optimization(PSO)algorithm is proposed to address the issue of false data injection(FDI)attack detection in the load frequency control(LFC)system under parameter uncertainty.Firstly,a state estimation model for the LFC system is established based on Kalman filtering.To assist theχ^(2)detector in identifying FDI attacks,a transmission strategy of adding a pseudo-random watermark matrix during information transmission is proposed.Prior to transmission,the transmitting terminal multiplies the measurement to be transmitted by a pseudo-random matrix.Subsequently,the receiving terminal decrypts the received data to retrieve the genuine information.Compared with traditional methods,this strategy neither increases computational complexity nor sacrifices estimation performance in the absence of attacks.When an FDI attack occurs,the system’s measurement signals are maliciously tampered with by attackers.During the decryption process at the receiver end,a unique coupling relationship emerges between the pre-embedded watermark matrix and the injected attack signal.This coupling feature is highly distinguishable by the detector,enabling rapid and accurate identification of FDI attacks and thus ensuring the efficient and stable operation of the LFC system.Furthermore,to tackle the parameter uncertainty inherent in LFC systems(a factor that may degrade the accuracy of state estimation and attack detection),the PSO algorithm is introduced for online parameter identification.This algorithm optimizes the key parameters of the LFC system in real time,significantly improving the matching degree between the established state estimation model and the actual operating system.Finally,by fusing the watermarkingbased attack detection strategy and the PSO-based parameter identification technique,a complete online FDI attack identification and detection method for LFC systems is formed.The effectiveness and feasibility of the proposed method are verified through simulations on a two-area LFC system.