Sparsified Secure Aggregation for Privacy-Preserving Federated Learning

Sparsified Secure Aggregation for Privacy-Preserving Federated Learning

23 December 2021

Papers citing "Sparsified Secure Aggregation for Privacy-Preserving Federated Learning"

15 / 15 papers shown

Title
SecEmb: Sparsity-Aware Secure Federated Learning of On-Device Recommender System with Large Embedding Peihua Mai Youlong Ding Ziyan Lyu Minxin Du Yan Pang FedML 0 0 0 18 May 2025
Sparsification Under Siege: Defending Against Poisoning Attacks in Communication-Efficient Federated Learning Zhiyong Jin Runhua Xu Chong Li Y. Liu Jianxin Li AAML FedML 39 0 0 30 Apr 2025
Secure Aggregation Meets Sparsification in Decentralized Learning Sayan Biswas Anne-Marie Kermarrec Rafael Pires Rishi Sharma Milos Vujasinovic 44 0 0 13 May 2024
Federated learning with differential privacy and an untrusted aggregator Kunlong Liu Trinabh Gupta 47 0 0 17 Dec 2023
Towards Efficient Secure Aggregation in FL: Partial Vector Freezing for Cost Compression Siqing Zhang Yong Liao Pengyuan Zhou 27 0 0 08 Dec 2023
LISA: LIghtweight single-server Secure Aggregation with a public source of randomness Elina van Kempen Qifei Li G. Marson Claudio Soriente 25 5 0 04 Aug 2023
Efficient Secure Aggregation for Privacy-Preserving Federated Machine Learning R. Behnia Mohammadreza Ebrahimi Arman Riasi Sherman S. M. Chow B. Padmanabhan Thang Hoang 23 6 0 07 Apr 2023
FedREP: A Byzantine-Robust, Communication-Efficient and Privacy-Preserving Framework for Federated Learning Yi-Rui Yang Kun Wang Wulu Li FedML 29 3 0 09 Mar 2023
Machine Unlearning of Federated Clusters Chao Pan Jin Sima Saurav Prakash Vishal Rana O. Milenkovic FedML MU 39 25 0 28 Oct 2022
How Much Privacy Does Federated Learning with Secure Aggregation Guarantee? A. Elkordy Jiang Zhang Yahya H. Ezzeldin Konstantinos Psounis A. Avestimehr FedML 35 38 0 03 Aug 2022
Federated Progressive Sparsification (Purge, Merge, Tune)+ Dimitris Stripelis Umang Gupta Greg Ver Steeg J. Ambite FedML 23 9 0 26 Apr 2022
Privacy-Preserving Aggregation in Federated Learning: A Survey Ziyao Liu Jiale Guo Wenzhuo Yang Jiani Fan Kwok-Yan Lam Jun Zhao FedML 32 87 0 31 Mar 2022
OLIVE: Oblivious Federated Learning on Trusted Execution Environment against the risk of sparsification Fumiyuki Kato Yang Cao Masatoshi Yoshikawa FedML 24 5 0 15 Feb 2022
Information Theoretic Secure Aggregation with User Dropouts Yizhou Zhao Hua Sun FedML 59 67 0 19 Jan 2021
The Future of Digital Health with Federated Learning Nicola Rieke Jonny Hancox Wenqi Li Fausto Milletari H. Roth ... Ronald M. Summers Andrew Trask Daguang Xu Maximilian Baust M. Jorge Cardoso OOD 174 1,707 0 18 Mar 2020