FedSurrogate: Backdoor Defense in Federated Learning via Layer Criticality and Surrogate Replacement

FedSurrogate: Backdoor Defense in Federated Learning via Layer Criticality and Surrogate Replacement arXiv:2605.11122v1 Announce Type: new Abstract: Federated Learning remains highly susceptible to backdoor attacks--malicious clients inject targeted behaviours into the global model. Existing defenses suffer from substantial false-positive rates under realistic non-independent and identically distributed (non-IID) data, incorrectly flagging benign clients and degrading model …

https://arxiv.org/abs/2605.11122

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