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A novel and universal GAN-based countermeasure to recover adversarial examples to benign examples.

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Title: A novel and universal GAN-based countermeasure to recover adversarial examples to benign examples.
Authors: Yang, Rui1,2, Cao, Tian-Jie1,2, tjcao@cumt.edu.cn, Chen, Xiu-Qing3, Zhang, Feng-Rong1,2
Source: Computers & Security; Dec2021, Vol. 111, pN.PAG-N.PAG, 1p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 153248285
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: A novel and universal GAN-based countermeasure to recover adversarial examples to benign examples.
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  Data: <searchLink fieldCode="JN" term="%22Computers+%26+Security%22">Computers & Security</searchLink>; Dec2021, Vol. 111, pN.PAG-N.PAG, 1p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=153248285
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.cose.2021.102457
    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 1
        StartPage: N.PAG
    Titles:
      – TitleFull: A novel and universal GAN-based countermeasure to recover adversarial examples to benign examples.
        Type: main
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      – PersonEntity:
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            NameFull: Yang, Rui
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            NameFull: Cao, Tian-Jie
      – PersonEntity:
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            NameFull: Chen, Xiu-Qing
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            NameFull: Zhang, Feng-Rong
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          Dates:
            – D: 01
              M: 12
              Text: Dec2021
              Type: published
              Y: 2021
          Identifiers:
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              Value: 01674048
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            – Type: volume
              Value: 111
          Titles:
            – TitleFull: Computers & Security
              Type: main
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