期刊名称：International Journal of Early Childhood Special Education
电子版ISSN：1308-5581
出版年度：2022
卷号：14
期号：5
页码：718-729
DOI：10.9756/INTJECSE/V14I5.71
语种：English
出版社：International Journal of Early Childhood Special Education
摘要：Using spatiotemporal patterns, this letter provides a flexible machine learning detection strategy for cyberattacks in distribution systems. Based on system-wide observations, the graph Laplacian detects spatiotemporal patterns. When cyberattacks happen, a flexible Bayes classifier (BC) teaches spatiotemporal practices, resulting in a violation. Flexible BCs used online can potentially be used to detect cyberattacks. Through the use of common IEEE 13- and 123-node test feeds, the effectiveness of the devised approach is shown. In order to anticipate load under cyberattacks, this research presents a machine learning-based anomaly detection (MLAD) technique.
