Anomaly detection of smart grid stealing network attacks based on deep autoencoder

Existing anomaly detectors in AMIs suffer from shallow architectures, which impede their ability to capture temporal correlations and complex patterns in electricity consumption data, thus impact detection performance adversely. A deep (stacked) autoencoder structure based on Long Short-Term Memory...

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Bibliographic Details
Main Authors: Huang Yan, Li Jincan, Yang Xiaqin, Li Pei, Li Zi
Format: Article
Language:Chinese
Published: National Computer System Engineering Research Institute of China 2024-02-01
Series:Dianzi Jishu Yingyong
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Online Access:http://www.chinaaet.com/article/3000163482
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