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Fed-DTCN: A Federated Disentangled Learning Framework for Unsupervised Zero-Day Anomaly Detection in IoT with Semantic-Aware Augmentation.

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Title: Fed-DTCN: A Federated Disentangled Learning Framework for Unsupervised Zero-Day Anomaly Detection in IoT with Semantic-Aware Augmentation.
Authors: Khan, Muhammad Ali1 (AUTHOR), Khalid, Osman1,2 (AUTHOR), Rais, Rao Naveed Bin1,2 (AUTHOR) r.rais@ajman.ac.ae
Source: Sensors (14248220). Mar2026, Vol. 26 Issue 6, p1918. 30p.
Database: Academic Search Ultimate
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  Data: Fed-DTCN: A Federated Disentangled Learning Framework for Unsupervised Zero-Day Anomaly Detection in IoT with Semantic-Aware Augmentation.
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  Data: <searchLink fieldCode="JN" term="%22Sensors+%2814248220%29%22">Sensors (14248220)</searchLink>. Mar2026, Vol. 26 Issue 6, p1918. 30p.
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        Value: 10.3390/s26061918
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      – TitleFull: Fed-DTCN: A Federated Disentangled Learning Framework for Unsupervised Zero-Day Anomaly Detection in IoT with Semantic-Aware Augmentation.
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              Text: Mar2026
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