88 citations · 301 across the 21 of their papers we have counts for
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cs.LG2019★ 88 cited
Federated Learning with Differential Privacy: Algorithms and Performance Analysis
Kang Wei, Jun Li, Ming Ding +6
In this paper, to effectively prevent information leakage, we propose a novel framework based on the concept of differential privacy (DP), in which artificial noises are added to t…
cs.NI2019★ 17 cited
On Safeguarding Privacy and Security in the Framework of Federated Learning
Chuan Ma, Jun Li, Ming Ding +4
Motivated by the advancing computational capacity of wireless end-user equipment (UE), as well as the increasing concerns about sharing private data, a new machine learning (ML) pa…