Comments on 'APFed: Anti-Poisoning Attacks in Privacy-Preserving Heterogeneous Federated Learning'

초록

Chen et al.(2023) proposed a method called APFed, which leverages additive homomorphic encryption to encrypt each client's gradient, aiming to prevent information leakage while effectively defending against poisoning attacks. In this paper, we demonstrate a fundamental flaw in the authors' claim of security proof yielding that the proposed APFed method is insecure.

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