DHSA: Efficient Doubly Homomorphic Secure Aggregation for Cross-silo
Federated Learning

DHSA: Efficient Doubly Homomorphic Secure Aggregation for Cross-silo Federated Learning

15 August 2022

Jing Ye

Papers citing "DHSA: Efficient Doubly Homomorphic Secure Aggregation for Cross-silo Federated Learning"

6 / 6 papers shown

Title
POSEIDON: Privacy-Preserving Federated Neural Network Learning Sinem Sav Apostolos Pyrgelis J. Troncoso-Pastoriza D. Froelicher Jean-Philippe Bossuat João Sá Sousa Jean-Pierre Hubaux FedML 30 155 0 01 Sep 2020
Scalable Privacy-Preserving Distributed Learning D. Froelicher J. Troncoso-Pastoriza Apostolos Pyrgelis Sinem Sav João Sá Sousa Jean-Philippe Bossuat Jean-Pierre Hubaux FedML 50 69 0 19 May 2020
Federated Learning with Differential Privacy: Algorithms and Performance Analysis Kang Wei Jun Li Ming Ding Chuan Ma Heng Yang Farokhi Farhad Shi Jin Tony Q.S. Quek H. Vincent Poor FedML 91 1,589 0 01 Nov 2019
Federated Machine Learning: Concept and Applications Qiang Yang Yang Liu Tianjian Chen Yongxin Tong FedML 57 2,302 0 13 Feb 2019
LEAF: A Benchmark for Federated Settings S. Caldas Sai Meher Karthik Duddu Peter Wu Tian Li Jakub Konecný H. B. McMahan Virginia Smith Ameet Talwalkar FedML 104 1,410 0 03 Dec 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 178 8,807 0 25 Aug 2017