AINeutralarXiv – CS AI · 8h ago6/10
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AdaBFL: Multi-Layer Defensive Adaptive Aggregation for Bzantine-Robust Federated Learning
Researchers propose AdaBFL, a Byzantine-robust federated learning method that uses adaptive multi-layer defense mechanisms to protect distributed machine learning systems from poisoning attacks by malicious clients. The approach balances defense against multiple attack types without requiring server-side dataset access, with proven convergence properties on non-IID data.