Defending Against Backdoor Attacks via Alignment Checking in Model-Contrastive Federated Learning

Hongliang Zhang, Zhongyuan Yu, Guijuan Wang +4

The paper proposes FedDAB, a two‑phase defense for federated learning that uses contrastive regularization and alignment checking to detect and exclude malicious local updates caus…