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DOE OSTI · 1812898

Flexible Machine Learning-Based Cyberattack Detection Using Spatiotemporal Patterns for Distribution Systems

Abstract

This letter develops a flexible machine learning detection method for cyberattacks in distribution systems considering spatiotemporal patterns. Spatiotemporal patterns are recognized by the graph Laplacian based on system-wide measurements. A flexible Bayes classifier (BC) is used to train spatiotemporal patterns which could be violated when cyberattacks occur. Cyberattacks are detected by using flexible BCs online. The effectiveness of the developed method is demonstrated through standard IEEE 13- and 123-node test feeders.

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BibTeXRIS

Cui, Mingjian, Wang, Jianhui, Chen, Bo. 2020-03-01. Flexible Machine Learning-Based Cyberattack Detection Using Spatiotemporal Patterns for Distribution Systems. https://doi.org/10.1109/tsg.2020.2965797

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