Lightweight anomaly detection model for UAV networks based on memory-enhanced autoencoders
In order to solve the problems of high energy consumption and high reliance on manual annotation data of traditional intelligent attack detection methods in UAV networks, a lightweight UAV network online anomaly detection model based on a double-layer memory-enhanced autoencoder integrated architect...
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| Hauptverfasser: | , , , , , |
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| Format: | Artigo |
| Sprache: | Chinês |
| Veröffentlicht: |
Editorial Department of Journal on Communications
2024-04-01
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| Schriftenreihe: | Tongxin xuebao |
| Schlagworte: | |
| Online-Zugang: | http://www.joconline.com.cn/thesisDetails#10.11959/j.issn.1000-436x.2024011 |
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