RKD defends federated learning against backdoor attacks by clustering client updates with cosine similarity and HDBSCAN, selecting median-like models, and distilling their ensemble into the global model.
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Robust Knowledge Distillation in Federated Learning: Counteracting Backdoor Attacks
RKD defends federated learning against backdoor attacks by clustering client updates with cosine similarity and HDBSCAN, selecting median-like models, and distilling their ensemble into the global model.