Privacy-preserving Federated Learning based on Multi-key Homomorphic
Encryption

Privacy-preserving Federated Learning based on Multi-key Homomorphic Encryption

14 April 2021

Papers citing "Privacy-preserving Federated Learning based on Multi-key Homomorphic Encryption"

16 / 16 papers shown

Title
A Numerical Gradient Inversion Attack in Variational Quantum Neural-Networks Georgios Papadopoulos Shaltiel Eloul Yash Satsangi Jamie Heredge Niraj Kumar Chun-Fu Chen Marco Pistoia 81 0 0 17 Apr 2025
PriRoAgg: Achieving Robust Model Aggregation with Minimum Privacy Leakage for Federated Learning Sizai Hou Songze Li Tayyebeh Jahani-Nezhad Giuseppe Caire FedML 74 2 0 12 Jul 2024
FLEAM: A Federated Learning Empowered Architecture to Mitigate DDoS in Industrial IoT J. Li Lingjuan Lyu X. Liu X. Zhang X. Lyu 38 115 0 11 Dec 2020
Deep Leakage from Gradients Ligeng Zhu Zhijian Liu Song Han FedML 52 2,185 0 21 Jun 2019
Federated Machine Learning: Concept and Applications Qiang Yang Yang Liu Tianjian Chen Yongxin Tong FedML 45 2,297 0 13 Feb 2019
Drynx: Decentralized, Secure, Verifiable System for Statistical Queries and Machine Learning on Distributed Datasets D. Froelicher J. Troncoso-Pastoriza João Sá Sousa Jean-Pierre Hubaux OOD SyDa 48 49 0 11 Feb 2019
Federated Learning with Non-IID Data Yue Zhao Meng Li Liangzhen Lai Naveen Suda Damon Civin Vikas Chandra FedML 132 2,547 0 02 Jun 2018
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 113 1,461 0 10 May 2018
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett OOD FedML 67 1,483 0 05 Mar 2018
Differentially Private Federated Learning: A Client Level Perspective Robin C. Geyer T. Klein Moin Nabi FedML 76 1,287 0 20 Dec 2017
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning Briland Hitaj G. Ateniese Fernando Perez-Cruz FedML 95 1,385 0 24 Feb 2017
Practical Secure Aggregation for Federated Learning on User-Held Data Keith Bonawitz Vladimir Ivanov Ben Kreuter Antonio Marcedone H. B. McMahan Sarvar Patel Daniel Ramage Aaron Segal Karn Seth FedML 37 499 0 14 Nov 2016
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 253 4,620 0 18 Oct 2016
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 138 6,049 0 01 Jul 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 198 17,235 0 17 Feb 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 491 149,474 0 22 Dec 2014