PriRoAgg: Achieving Robust Model Aggregation with Minimum Privacy
Leakage for Federated Learning

PriRoAgg: Achieving Robust Model Aggregation with Minimum Privacy Leakage for Federated Learning

12 July 2024

Songze Li

Tayyebeh Jahani-Nezhad

Papers citing "PriRoAgg: Achieving Robust Model Aggregation with Minimum Privacy Leakage for Federated Learning"

7 / 7 papers shown

Title
DReS-FL: Dropout-Resilient Secure Federated Learning for Non-IID Clients via Secret Data Sharing Jiawei Shao Yuchang Sun Songze Li Jun Zhang OOD 16 37 0 06 Oct 2022
Secure Byzantine-Robust Distributed Learning via Clustering R. K. Velicheti Derek Xia Oluwasanmi Koyejo FedML OOD 52 19 0 06 Oct 2021
LightSecAgg: a Lightweight and Versatile Design for Secure Aggregation in Federated Learning Jinhyun So Chaoyang He Chien-Sheng Yang Songze Li Qian-long Yu Ramy E. Ali Başak Güler Salman Avestimehr FedML 55 163 0 29 Sep 2021
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping Xiaoyu Cao Minghong Fang Jia Liu Neil Zhenqiang Gong FedML 102 610 0 27 Dec 2020
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 169 351 0 07 Dec 2020
Threats to Federated Learning: A Survey Lingjuan Lyu Han Yu Qiang Yang FedML 186 432 0 04 Mar 2020
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 177 1,031 0 29 Nov 2018