Two-Phase Multi-Party Computation Enabled Privacy-Preserving Federated Learning

25 May 2020

Papers citing "Two-Phase Multi-Party Computation Enabled Privacy-Preserving Federated Learning"

5 / 5 papers shown

Title
NET-SA: An Efficient Secure Aggregation Architecture Based on In-Network Computing Qingqing Ren Wen Wang Shuyong Zhu Zhiyuan Wu Yujun Zhang 40 0 0 02 Jan 2025
Federated Learning: A Cutting-Edge Survey of the Latest Advancements and Applications Azim Akhtarshenas Mohammad Ali Vahedifar Navid Ayoobi B. Maham Tohid Alizadeh Sina Ebrahimi David López-Pérez FedML 41 5 0 08 Oct 2023
BFRT: Blockchained Federated Learning for Real-time Traffic Flow Prediction Collin Meese Hang Chen Syed Ali Asif Wanxin Li Chien-Chung Shen Mark M. Nejad 41 22 0 28 May 2023
Balancing Privacy Protection and Interpretability in Federated Learning Zhe Li Honglong Chen Zhichen Ni Huajie Shao FedML 16 8 0 16 Feb 2023
Enigma: Decentralized Computation Platform with Guaranteed Privacy Guy Zyskind Oz Nathan Alex Pentland MoE FedML 35 445 0 10 Jun 2015