Secure and Privacy-Preserving Federated Learning via Co-Utility

4 August 2021

Papers citing "Secure and Privacy-Preserving Federated Learning via Co-Utility"

6 / 6 papers shown

Title
AnoFel: Supporting Anonymity for Privacy-Preserving Federated Learning Ghada Almashaqbeh Zahra Ghodsi FedML 29 1 0 12 Jun 2023
Enhanced Security and Privacy via Fragmented Federated Learning N. Jebreel J. Domingo-Ferrer Alberto Blanco-Justicia David Sánchez FedML 26 26 0 13 Jul 2022
Edge Learning for B5G Networks with Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing Wei Xu Zhaohui Yang Derrick Wing Kwan Ng Marco Levorato Yonina C. Eldar Mérouane Debbah 28 398 0 01 Jun 2022
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey Shangwei Guo Xu Zhang Feiyu Yang Tianwei Zhang Yan Gan Tao Xiang Yang Liu FedML 28 9 0 19 Dec 2021
PPT: A Privacy-Preserving Global Model Training Protocol for Federated Learning in P2P Networks Qian Chen Zilong Wang Wenjing Zhang Xiaodong Lin FedML 28 16 0 30 May 2021
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 182 1,032 0 29 Nov 2018