LAUSR

Securing Distributed SGD Against Gradient Leakage Threats

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1 Published in 2023 at "IEEE Transactions on Parallel and Distributed Systems"

DOI: 10.1109/tpds.2023.3273490

Abstract: This paper presents a holistic approach to gradient leakage resilient distributed Stochastic Gradient Descent (SGD). First, we analyze two types of strategies for privacy-enhanced federated learning: (i) gradient pruning with random selection or low-rank filtering… read more here.

Keywords: securing distributed; privacy; gradient leakage; gradient ... See more keywords