FL-WBC: EnhancingRobustnessagainstModel PoisoningAttacksinFederatedLearningfroma ClientPerspective

Neural Information Processing Systems 

Federated learning (FL) is a popular distributed learning framework that trains a global model through iterative communications between a central server and edge devices. Recent works have demonstrated that FL is vulnerable to model poisoning attacks.

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