A client-side adversarial-trigger search plus model patching reduces backdoor attack success in federated learning to near zero on MNIST and Fashion-MNIST, with the largest gains over server-side defenses in non-i.i.d. settings.
Federated learning for health- care: Systematic review and architecture proposal
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Client-Side Patching against Backdoor Attacks in Federated Learning
A client-side adversarial-trigger search plus model patching reduces backdoor attack success in federated learning to near zero on MNIST and Fashion-MNIST, with the largest gains over server-side defenses in non-i.i.d. settings.