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FUSE is introduced, a structure-aware robust aggregator that uses a small trusted labeled dataset for coefficient recovery, scale and cone-consistency screening, and post-screening step-size control, and improves seed-wise worst-attack accuracy over the strongest baseline on each benchmark by 3.9--30.1 percentage point...
This article proposes a novel adaptive obfuscation mechanism, coined FedAdOb, to protect private data without yielding original model performances, and utilizes passport-based adaptive obfuscation to ensure data privacy in both horizontal and vertical federated learning settings.
The proposed FedMGP+ effectively mitigates forgetting, significantly enhances personalized performance, and provides robust defense against poisoning and gradient leakage attacks.
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