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cs.CR2026
SpooFL: Spoofing Federated Learning
Isaac Baglin, Xiatian Zhu, Simon Hadfield
Traditional defenses against Deep Leakage (DL) attacks in Federated Learning (FL) primarily focus on obfuscation, introducing noise, transformations or encryption to degrade an att…
cs.CR2025
FEDLAD: Federated Evaluation of Deep Leakage Attacks and Defenses
Isaac Baglin, Xiatian Zhu, Simon Hadfield
Federated Learning is a privacy preserving decentralized machine learning paradigm designed to collaboratively train models across multiple clients by exchanging gradients to the s…