XFED is the first aggregation-agnostic non-collusive model poisoning attack that bypasses eight state-of-the-art defenses on six benchmark datasets without attacker coordination.
Manipulating machine learn- ing: Poisoning attacks and countermeasures for regression learning
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XFED: Non-Collusive Model Poisoning Attack Against Byzantine-Robust Federated Classifiers
XFED is the first aggregation-agnostic non-collusive model poisoning attack that bypasses eight state-of-the-art defenses on six benchmark datasets without attacker coordination.