Wenshuo Ma
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126
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2026
Defending Against Backdoor Attacks via Alignment Checking in Model-Contrastive Federated Learning
This paper proposes FedDAB, a two-phase method for defending Federated Learning against backdoor attacks using local contrastive regularization and alignment checking.
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cs.CRcs.AIcs.LGNEWEmpiricalJul 29, 2026
Defending Against Backdoor Attacks via Alignment Checking in Model-Contrastive Federated Learning
Hongliang Zhang, Zhongyuan Yu, Guijuan Wang, Tianqing He +3 more
This paper proposes FedDAB, a two-phase method for defending Federated Learning against backdoor attacks using local contrastive regularization and alignment checking.
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