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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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
National Computer System Engineering Research Institute of China
2024-02-01
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| Series: | Dianzi Jishu Yingyong |
| Subjects: | |
| Online Access: | http://www.chinaaet.com/article/3000163482 |
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