HIGHLIGHTS
- who: J. JITHISH and colleagues from the Engineering Product Development Pillar, Singapore University of Technology Design, Singapore , have published the research: Distributed Anomaly Detection in Smart Grids: A Federated Learning-Based Approach, in the Journal: (JOURNAL) of June/30,/2013
- what: Motivated by these concerns the authors propose a Federated Learning (FL)-based smart grid anomaly detection scheme where ML models are trained locally in smart meters without sharing data with a central server thus ensuring user privacy. Using standard datasets the authors investigate the anomaly detection performance of federated learning observe that FL models . . .
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