卡尔曼滤波器
残余物
计算机科学
探测器
智能电网
滤波器(信号处理)
实时计算
控制理论(社会学)
人工智能
数据挖掘
计算机视觉
工程类
算法
控制(管理)
电信
电气工程
出处
期刊:IEEE Transactions on Control of Network Systems
[Institute of Electrical and Electronics Engineers]
日期:2022-09-01
卷期号:9 (3): 1238-1250
被引量:22
标识
DOI:10.1109/tcns.2022.3141026
摘要
As one of the most dangerous cyber attacks in smart grids, the false data injection attacks pose a serious threat to power system security. To detect the false data, the traditional residual method and other improved methods, such as the Kalman-filter-based detector, have been proposed. However, these methods often have defects, especially in a very complex networked system with noises. By investigating the tolerance to the uncertainty in the residual detection method and properties of noises, the attack magnitude planning has been presented to hide the attack behind noises, which can bypass the residual detection method. As to the Kalman-filter-based detector, this article designs a specific attack strategy that can successfully deceive the Kalman-filter-based detector. Under this strategy, the false data injected at each step are used to balance the anomalies caused by previous false data, making the system look quite normal in monitoring, while deviating the system from normal operation eventually.
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