Web: http://arxiv.org/abs/2105.00529

Jan. 7, 2022, 2:20 a.m. | Hanchi Ren, Jingjing Deng, Xianghua Xie

cs.CR updates on arXiv.org arxiv.org

Data privacy has become an increasingly important issue in Machine Learning
(ML), where many approaches have been developed to tackle this challenge, e.g.
cryptography (Homomorphic Encryption (HE), Differential Privacy (DP), etc.) and
collaborative training (Secure Multi-Party Computation (MPC), Distributed
Learning and Federated Learning (FL)). These techniques have a particular focus
on data encryption or secure local computation. They transfer the intermediate
information to the third party to compute the final result. Gradient exchanging
is commonly considered to be a secure …

attack data data leakage learning network neural network

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