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Xianxun Yao

1 accepted papers

2024

GI-PIP: Do We Require Impractical Auxiliary Dataset for Gradient Inversion Attacks?

ICASSP 2024accepted

Deep gradient inversion attacks expose a serious threat to Federated Learning (FL) by accurately recovering private data from shared gradients. However, the state-of-the-art heavily relies on impractical assumptions to access excessive auxiliary data, which violates the basic data partitioning princ…

Cited by 0SourceScholar