Hammer and Anvil framework categorizes backdoors by update deviation δ and shows that principled combinations of Type-1 outlier/robust and Type-2 removal defenses resist full-information adaptive adversaries.
A survey on vulnerability of federated learn- ing: A learning algorithm perspective.Neurocomputing, 573:127225
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Hammer and Anvil: Toward a Theory of Backdoors in Federated Learning
Hammer and Anvil framework categorizes backdoors by update deviation δ and shows that principled combinations of Type-1 outlier/robust and Type-2 removal defenses resist full-information adaptive adversaries.