Deep Leakage from Gradients

Deep Leakage from Gradients

21 June 2019

Zhijian Liu

Song Han

Papers citing "Deep Leakage from Gradients"

18 / 368 papers shown

Title
Learn distributed GAN with Temporary Discriminators Hui Qu Yikai Zhang Qi Chang Zhennan Yan Chao Chen Dimitris N. Metaxas FedML 21 16 0 17 Jul 2020
Data Poisoning Attacks Against Federated Learning Systems Vale Tolpegin Stacey Truex Mehmet Emre Gursoy Ling Liu FedML 28 639 0 16 Jul 2020
A Survey of Privacy Attacks in Machine Learning M. Rigaki Sebastian Garcia PILM AAML 39 213 0 15 Jul 2020
Quality Inference in Federated Learning with Secure Aggregation Balázs Pejó G. Biczók FedML 21 22 0 13 Jul 2020
Differentially private cross-silo federated learning Mikko A. Heikkilä A. Koskela Kana Shimizu Samuel Kaski Antti Honkela FedML 29 24 0 10 Jul 2020
Gradient-EM Bayesian Meta-learning Yayi Zou Xiaoqi Lu BDL 33 16 0 21 Jun 2020
Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks Lixin Fan Kam Woh Ng Ce Ju Tianyu Zhang Chang Liu Chee Seng Chan Qiang Yang MIACV 17 63 0 20 Jun 2020
Topology-aware Differential Privacy for Decentralized Image Classification Shangwei Guo Tianwei Zhang Guowen Xu Hanzhou Yu Tao Xiang Yang Liu 22 18 0 14 Jun 2020
Dataset Condensation with Gradient Matching Bo Zhao Konda Reddy Mopuri Hakan Bilen DD 36 477 0 10 Jun 2020
Secure Byzantine-Robust Machine Learning Lie He Sai Praneeth Karimireddy Martin Jaggi OOD 18 58 0 08 Jun 2020
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning Xinjian Luo Xiangqi Zhu FedML 73 25 0 27 Apr 2020
Adversarial Attacks and Defenses: An Interpretation Perspective Ninghao Liu Mengnan Du Ruocheng Guo Huan Liu Xia Hu AAML 26 8 0 23 Apr 2020
An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies David Enthoven Zaid Al-Ars FedML 60 50 0 01 Apr 2020
User-Level Privacy-Preserving Federated Learning: Analysis and Performance Optimization Kang Wei Jun Li Ming Ding Chuan Ma Hang Su Bo-Wen Zhang H. Vincent Poor FedML 25 11 0 29 Feb 2020
Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees Richeng Jin Yufan Huang Xiaofan He H. Dai Tianfu Wu FedML 22 63 0 25 Feb 2020
Turbo-Aggregate: Breaking the Quadratic Aggregation Barrier in Secure Federated Learning Jinhyun So Başak Güler A. Avestimehr FedML 27 289 0 11 Feb 2020
Multi-site fMRI Analysis Using Privacy-preserving Federated Learning and Domain Adaptation: ABIDE Results Xiaoxiao Li Yufeng Gu Nicha Dvornek Lawrence H. Staib P. Ventola James S. Duncan FedML OOD 18 353 0 16 Jan 2020
Secure Federated Submodel Learning Chaoyue Niu Fan Wu Shaojie Tang Lifeng Hua Rongfei Jia Chengfei Lv Zhihua Wu Guihai Chen FedML 14 30 0 06 Nov 2019