Electricity Theft Detection for Smart Homes: Harnessing the Power of Machine Learning With Real and Synthetic Attacks

Electricity theft is a pervasive issue with economic implications that necessitate innovative approaches for its detection, given the critical challenge of limited labeled data. However, connecting smart home devices introduces numerous vectors for electricity theft. Therefore, this study introduces...

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Bibliographic Details

Main Authors:	Olufemi Abiodun Abraham, Hideya Ochiai, Md. Delwar Hossain, Yuzo Taenaka, Youki Kadobayashi
Format:	Artigo
Language:	Inglês
Published:	IEEE 2024-01-01
Series:	IEEE Access
Subjects:	Electricity theft detection machine learning synthetic attack data smart home real attack data unsupervised learning
Online Access:	https://ieeexplore.ieee.org/document/10436697/
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