High-Fidelity Gradient Inversion in Distributed Learning
Zipeng Ye,
Wenjian Luo,
Qi Zhou
et al.
Abstract:Distributed learning frameworks aim to train global models by sharing gradients among clients while preserving the data privacy of each individual client. However, extensive research has demonstrated that these learning frameworks do not absolutely ensure the privacy, as training data can be reconstructed from shared gradients. Nevertheless, the existing privacy-breaking attack methods have certain limitations. Some are applicable only to small models, while others can only recover images in small batch size a… Show more
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