most citedToward Secure and Private Over-the-Air Federated Learning

2 citations · 3 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2023★ 1 cited

Over-the-Air Federated Averaging with Limited Power and Privacy Budgets

Na Yan, Kezhi Wang, Cunhua Pan +3

To jointly overcome the communication bottleneck and privacy leakage of wireless federated learning (FL), this paper studies a differentially private over-the-air federated averagi…

eess.SP2022

Device Scheduling for Over-the-Air Federated Learning with Differential Privacy

Na Yan, Kezhi Wang, Cunhua Pan +1

In this paper, we propose a device scheduling scheme for differentially private over-the-air federated learning (DP-OTA-FL) systems, referred to as S-DPOTAFL, where the privacy of…

eess.SP2022★ 2 cited

Toward Secure and Private Over-the-Air Federated Learning

Na Yan, Kezhi Wang, Kangda Zhi +3

In this paper, a novel secure and private over-the-air federated learning (SP-OTA-FL) framework is studied where noise is employed to protect data privacy and system security. Spec…