Research Article
An Introductory Review Of Anomaly Detection Methods In Smart Grids
@INPROCEEDINGS{10.4108/eai.7-12-2021.2314604, author={Preethi G and Anitha Kumari K}, title={An Introductory Review Of Anomaly Detection Methods In Smart Grids }, proceedings={Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India}, publisher={EAI}, proceedings_a={ICCAP}, year={2021}, month={12}, keywords={machine learning smart grids supervised learning unsupervised learning anomaly detection}, doi={10.4108/eai.7-12-2021.2314604} }- Preethi G
Anitha Kumari K
Year: 2021
An Introductory Review Of Anomaly Detection Methods In Smart Grids
ICCAP
EAI
DOI: 10.4108/eai.7-12-2021.2314604
Abstract
Cyber Physical systems such as smart grids have the potential to address the future energy crisis. Because of the bidirectional flow of information across various domains in a smart grid, anomaly detection is one of the prime security related challenges. Machine learning models have emerged as one of the prospective artificial intelligence technologies to model supervised and unsupervised data for analysis and prediction. This paper reviews the various anomaly detection schemes in a Smart Grid Infrastructure based on machine learning techniques.
Copyright © 2021–2024 EAI
