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Anomaly detection and defense techniques in federated learning: a comprehensive review.

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Title: Anomaly detection and defense techniques in federated learning: a comprehensive review.
Authors: Zhang, Chang1, Yang, Shunkun2, ysk@buaa.edu.cn, Mao, Lingfeng1, Ning, Huansheng1
Source: Artificial Intelligence Review; Jun2024, Vol. 57 Issue 6, p1-34, 34p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 177447878
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PubType: Academic Journal
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  Data: Anomaly detection and defense techniques in federated learning: a comprehensive review.
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  Data: <searchLink fieldCode="JN" term="%22Artificial+Intelligence+Review%22">Artificial Intelligence Review</searchLink>; Jun2024, Vol. 57 Issue 6, p1-34, 34p
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      – Type: doi
        Value: 10.1007/s10462-024-10796-1
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      – Code: eng
        Text: English
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        PageCount: 34
        StartPage: 1
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      – TitleFull: Anomaly detection and defense techniques in federated learning: a comprehensive review.
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            NameFull: Zhang, Chang
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            NameFull: Yang, Shunkun
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            NameFull: Mao, Lingfeng
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              Text: Jun2024
              Type: published
              Y: 2024
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              Value: 57
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