Efficient Byzantine-Robust and Provably Privacy-Preserving Federated Learning

29 July 2024

Papers citing "Efficient Byzantine-Robust and Provably Privacy-Preserving Federated Learning"

20 / 20 papers shown

Title
Universally Harmonizing Differential Privacy Mechanisms for Federated Learning: Boosting Accuracy and Convergence Shuya Feng Meisam Mohammady Hanbin Hong Shenao Yan Ashish Kundu Binghui Wang Yuan Hong FedML 86 3 0 20 Jul 2024
Inf2Guard: An Information-Theoretic Framework for Learning Privacy-Preserving Representations against Inference Attacks Sayedeh Leila Noorbakhsh Binghui Zhang Yuan Hong Binghui Wang AAML 100 10 0 04 Mar 2024
Task-Agnostic Privacy-Preserving Representation Learning for Federated Learning Against Attribute Inference Attacks Caridad Arroyo Arevalo Sayedeh Leila Noorbakhsh Yun Dong Yuan Hong Binghui Wang 98 16 0 12 Dec 2023
FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients Zaixi Zhang Xiaoyu Cao Jin Jia Neil Zhenqiang Gong AAML FedML 94 224 0 19 Jul 2022
Bayesian Framework for Gradient Leakage Mislav Balunović Dimitar I. Dimitrov Robin Staab Martin Vechev FedML 71 43 0 08 Nov 2021
Gradient Inversion with Generative Image Prior Jinwoo Jeon Jaechang Kim Kangwook Lee Sewoong Oh Jungseul Ok 77 158 0 28 Oct 2021
Learning from History for Byzantine Robust Optimization Sai Praneeth Karimireddy Lie He Martin Jaggi FedML AAML 98 182 0 18 Dec 2020
R-GAP: Recursive Gradient Attack on Privacy Junyi Zhu Matthew Blaschko FedML 54 137 0 15 Oct 2020
Inverting Gradients -- How easy is it to break privacy in federated learning? Jonas Geiping Hartmut Bauermeister Hannah Dröge Michael Moeller FedML 121 1,234 0 31 Mar 2020
iDLG: Improved Deep Leakage from Gradients Bo Zhao Konda Reddy Mopuri Hakan Bilen FedML 81 643 0 08 Jan 2020
Robust Aggregation for Federated Learning Krishna Pillutla Sham Kakade Zaïd Harchaoui FedML 139 669 0 31 Dec 2019
Federated Variance-Reduced Stochastic Gradient Descent with Robustness to Byzantine Attacks Zhaoxian Wu Qing Ling Tianyi Chen G. Giannakis FedML AAML 114 185 0 29 Dec 2019
Local Model Poisoning Attacks to Byzantine-Robust Federated Learning Minghong Fang Xiaoyu Cao Jinyuan Jia Neil Zhenqiang Gong AAML OOD FedML 128 1,122 0 26 Nov 2019
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 129 1,628 0 01 Nov 2019
Towards Federated Learning at Scale: System Design Keith Bonawitz Hubert Eichner W. Grieskamp Dzmitry Huba A. Ingerman ... H. B. McMahan Timon Van Overveldt David Petrou Daniel Ramage Jason Roselander FedML 128 2,676 0 04 Feb 2019
RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets Liping Li Canran Xu Xiangnan He Yixin Cao Tat-Seng Chua FedML 128 600 0 09 Nov 2018
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 159 1,486 0 10 May 2018
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett OOD FedML 133 1,520 0 05 Mar 2018
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning Briland Hitaj G. Ateniese Fernando Perez-Cruz FedML 141 1,413 0 24 Feb 2017
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 414 17,615 0 17 Feb 2016