CLB-Defense: based on contrastive learning defense for graph neural network against backdoor attack

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- CLB-Defense: based on contrastive learning defense for graph neural network against backdoor attack
- Journal on Communications Vol. 44, Issue 4, Pages: 154-166(2023)
- 作者机构：
  
  1. 浙江工业大学网络空间安全研究院，浙江杭州 310023
  2. 浙江工业大学信息工程学院，浙江杭州 310023
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(62072406);The Zhejiang Provincial Natural Science Foundation(LDQ23F020001);The Chinese National Key Laboratory of Science and Technology on Information System Secu-rity(61421110502);The Key Research and Development Program of Zhejiang Province(2022C01018)
- DOI：10.11959/j.issn.1000-436x.2023074
  CLC： TN92
- Online First：2023-04，
  
  Published：25 April 2023
- 稿件说明：
移动端阅览
Jinyin CHEN, Haiyang XIONG, Haonan MA, et al. CLB-Defense: based on contrastive learning defense for graph neural network against backdoor attack[J]. Journal on Communications, 2023, 44(4): 154-166.
DOI：

Jinyin CHEN, Haiyang XIONG, Haonan MA, et al. CLB-Defense: based on contrastive learning defense for graph neural network against backdoor attack[J]. Journal on Communications, 2023, 44(4): 154-166. DOI： 10.11959/j.issn.1000-436x.2023074.

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