Ming Xie

Fed-CBE: Client-Side Backdoor Elimination in Federated Learning via Persistent Parameter Disruption

Fed-CBE is proposed, a novel client-side defense algorithm that eliminates backdoors through three synergistic mechanisms: periodic alternating layer resetting disrupts deep parameters to dismantle cross-round backdoor accumulation, and indiscriminate forgetting employs entropy maximization on non-ground-truth classes to decouple backdoor associations without prior trigger knowledge.