Fed-DCR: A Backdoor Defense Scheme for Federated Learning Based on Dual-Domain Synergistic Detection

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更新时间：2026-07-13

- Fed-DCR: A Backdoor Defense Scheme for Federated Learning Based on Dual-Domain Synergistic Detection
- Journal on Communications (2026)
- 作者机构：
  
  1.河北大学网络空间安全与计算机学院，河北保定 071000
  2.河北金融学院金融科技学院，河北保定 071000
  3.华北电力大学英语系，河北保定 071000
- 作者简介：
  
  石朋亮，domyfate@hbu.edu.cn
- 基金信息：
  
  Beijing-Tianjin-Hebei Natural Science Foundation Cooperation Project(25JJJJC0037);Supported by Science Research Project of Hebei Education Department(QN2024200)
- DOI：10.11959/j.issn.1000-436x.TXXB260183
  CLC： TP309
- Received：08 April 2026，
  
  Revised：2026-07-09，
  
  Accepted：13 July 2026，
- 稿件说明：
移动端阅览
Kang Jie, Du Ruizhong, Liang Xiaoyan, et al. Fed-DCR: A Backdoor Defense Scheme for Federated Learning Based on Dual-Domain Synergistic Detection[J/OL]. Journal on Communications, 2026.
DOI：

Kang Jie, Du Ruizhong, Liang Xiaoyan, et al. Fed-DCR: A Backdoor Defense Scheme for Federated Learning Based on Dual-Domain Synergistic Detection[J/OL]. Journal on Communications, 2026. DOI： 10.11959/j.issn.1000-436x.TXXB260183.

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