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Federated deep learning for anomaly detection in the internet of things.

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Title: Federated deep learning for anomaly detection in the internet of things.
Authors: Wang, Xiaofeng1,2, Wang, Yonghong1,2, i20019777@student.newinti.edu.my, Javaheri, Zahra3, zahra.javaheri77@gmail.com, Almutairi, Laila4, l.almutairi@mu.edu.sa, Moghadamnejad, Navid3, navid.moghadamnejad@gmail.com, Younes, Osama S.5,6, o_younes@ut.edu.sa
Source: Computers & Electrical Engineering; May2023, Vol. 108, pN.PAG-N.PAG, 1p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 163995570
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=163995570
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.compeleceng.2023.108651
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      – Code: eng
        Text: English
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        PageCount: 1
        StartPage: N.PAG
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      – TitleFull: Federated deep learning for anomaly detection in the internet of things.
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            NameFull: Wang, Xiaofeng
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            NameFull: Wang, Yonghong
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            NameFull: Javaheri, Zahra
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            NameFull: Moghadamnejad, Navid
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            NameFull: Younes, Osama S.
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            – D: 01
              M: 05
              Text: May2023
              Type: published
              Y: 2023
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              Value: 108
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