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…