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.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
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
Cite the original work for its findings. Save a collection to share your selection of sources.