Smart Grid Security Enhancement by Using Belief Propagation
نویسندگان
چکیده
False data injection attack (FDIA) is a critical cyber-attack that can cause disrupt operations and subsequently blackouts in smart grid networks. Cleverly constructed stealthy false measurement vectors circumvent the bad detector unit mislead state estimation process. This article proposes novel belief propagation (BP)-based algorithm to detect both random stealthy-type FDIAs grids with higher detection rate than state-of-the-art machine learning classifiers such as Naive Bayes, support vector machines, Random Forest, OneR, AdaBoost. Another feature of proposed without using any historical data, which are sketchy due security constraints infinitesimal occurrence numbers. The BP method utilizes local sensor calculate send it message signal control center. Then, center determines final/global compares result predefined threshold value derived from uncompromised database. real-time steady-state load utilized for dc estimation. From obtained results, performance parameters rate, receiver operating characteristic curve, precision, recall, F-measure found superior aforementioned algorithms.
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ژورنال
عنوان ژورنال: IEEE Systems Journal
سال: 2021
ISSN: ['1932-8184', '1937-9234', '2373-7816']
DOI: https://doi.org/10.1109/jsyst.2020.3001951