iDLG: Improved Deep Leakage from Gradients

8 January 2020

Papers citing "iDLG: Improved Deep Leakage from Gradients"

49 / 349 papers shown

Title
Federated Learning for Privacy-Preserving Open Innovation Future on Digital Health Guodong Long Tao Shen Yue Tan Leah Gerrard Allison Clarke Jing Jiang FedML 110 54 0 24 Aug 2021
UnSplit: Data-Oblivious Model Inversion, Model Stealing, and Label Inference Attacks Against Split Learning Ege Erdogan Alptekin Kupcu A. E. Cicek FedML MIACV 98 97 0 20 Aug 2021
A Novel Attribute Reconstruction Attack in Federated Learning Lingjuan Lyu Chong Chen AAML 96 44 0 16 Aug 2021
Efficient Byzantine-Resilient Stochastic Gradient Desce Kaiyun Li Xiaojun Chen Ye Dong Peng Zhang Dakui Wang Shuai Zeng 68 0 0 15 Aug 2021
PRECODE - A Generic Model Extension to Prevent Deep Gradient LeakageIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2021 Daniel Scheliga Patrick Mäder M. Seeland MIACV 123 40 0 10 Aug 2021
Privacy-Preserving Machine Learning: Methods, Challenges and Directions Runhua Xu Nathalie Baracaldo J. Joshi 104 128 0 10 Aug 2021
Trustworthy AI: A Computational Perspective Haochen Liu Yiqi Wang Wenqi Fan Xiaorui Liu Yaxin Li Shaili Jain Yunhao Liu Anil K. Jain Shucheng Zhou FaML 264 240 0 12 Jul 2021
Differentially private federated deep learning for multi-site medical image segmentation Alexander Ziller Dmitrii Usynin Nicolas W. Remerscheid Moritz Knolle Marcus R. Makowski R. Braren Daniel Rueckert Georgios Kaissis FedML 99 26 0 06 Jul 2021
Optimizing the Numbers of Queries and Replies in Federated Learning with Differential Privacy Yipeng Zhou Xuezheng Liu Yao Fu Di Wu Chao Li Shui Yu FedML 106 2 0 05 Jul 2021
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential PrivacyInternational Conference on Machine Learning (ICML), 2021 Xinwei Zhang Xiangyi Chen Min-Fong Hong Zhiwei Steven Wu Jinfeng Yi FedML 123 111 0 25 Jun 2021
Federated Learning on Non-IID Data: A Survey Hangyu Zhu Jinjin Xu Shiqing Liu Yaochu Jin OOD FedML 184 986 0 12 Jun 2021
Quantifying and Localizing Usable Information Leakage from Neural Network Gradients Fan Mo Anastasia Borovykh Mohammad Malekzadeh Soteris Demetriou Deniz Gündüz Hamed Haddadi FedML 111 5 0 28 May 2021
Separation of Powers in Federated Learning P. Cheng Kevin Eykholt Zhongshu Gu Hani Jamjoom K.R. Jayaram Enriquillo Valdez Ashish Verma FedML 80 13 0 19 May 2021
User-Level Label Leakage from Gradients in Federated LearningProceedings on Privacy Enhancing Technologies (PoPETs), 2021 A. Wainakh Fabrizio G. Ventola Till Müßig Jens Keim Carlos Garcia Cordero Ephraim Zimmer Tim Grube Kristian Kersting M. Mühlhäuser FedML AAML 92 59 0 19 May 2021
PPCA: Privacy-preserving Principal Component Analysis Using Secure Multiparty Computation(MPC) Xiaoyu Fan Guosai Wang Kung Chen Xu He Weijiang Xu 83 9 0 17 May 2021
GRNN: Generative Regression Neural Network -- A Data Leakage Attack for Federated LearningACM Transactions on Intelligent Systems and Technology (ACM TIST), 2021 Hanchi Ren Jingjing Deng Xianghua Xie SILM AAML FedML 246 117 0 02 May 2021
From Distributed Machine Learning to Federated Learning: A SurveyKnowledge and Information Systems (KAIS), 2021 Ji Liu Jizhou Huang Yang Zhou Xuhong Li Shilei Ji Haoyi Xiong Dejing Dou FedML OOD 220 296 0 29 Apr 2021
A Method to Reveal Speaker Identity in Distributed ASR Training, and How to Counter ItIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2021 Trung D. Q. Dang Om Thakkar Swaroop Indra Ramaswamy Rajiv Mathews Peter Chin Franccoise Beaufays FedML 67 10 0 15 Apr 2021
See through Gradients: Image Batch Recovery via GradInversionComputer Vision and Pattern Recognition (CVPR), 2021 Hongxu Yin Arun Mallya Arash Vahdat J. Álvarez Jan Kautz Pavlo Molchanov FedML 181 532 0 15 Apr 2021
Constrained Differentially Private Federated Learning for Low-bandwidth DevicesConference on Uncertainty in Artificial Intelligence (UAI), 2021 Raouf Kerkouche G. Ács C. Castelluccia P. Genevès 100 7 0 27 Feb 2021
Proactive DP: A Multple Target Optimization Framework for DP-SGDInternational Conference on Machine Learning (ICML), 2021 Marten van Dijk Nhuong V. Nguyen Toan N. Nguyen Lam M. Nguyen Phuong Ha Nguyen 307 0 0 17 Feb 2021
Label Leakage and Protection in Two-party Split LearningInternational Conference on Learning Representations (ICLR), 2021 Oscar Li Jiankai Sun Xin Yang Weihao Gao Hongyi Zhang Junyuan Xie Virginia Smith Chong-Jun Wang FedML 259 162 0 17 Feb 2021
FLOP: Federated Learning on Medical Datasets using Partial NetworksKnowledge Discovery and Data Mining (KDD), 2021 Qiang Yang Jianyi Zhang Weituo Hao Gregory P. Spell Lawrence Carin FedML OOD 123 93 0 10 Feb 2021
Gain without Pain: Offsetting DP-injected Nosies Stealthily in Cross-device Federated LearningIEEE Internet of Things Journal (IEEE IoT Journal), 2021 Wenzhuo Yang Yipeng Zhou Maio Hu Di Wu J. Zheng Hui Wang Song Guo FedML 83 14 0 31 Jan 2021
On the Practicality of Differential Privacy in Federated Learning by Tuning Iteration Times Yao Fu Yipeng Zhou Di Wu Shui Yu Yonggang Wen Chao Li FedML 92 11 0 11 Jan 2021
Differentially Private Federated Learning for Cancer Prediction C. Béguier Jean Ogier du Terrail I. Meah M. Andreux Eric W. Tramel FedML 90 25 0 08 Jan 2021
Fidel: Reconstructing Private Training Samples from Weight Updates in Federated Learning David Enthoven Zaid Al-Ars FedML 155 15 0 01 Jan 2021
Communication-Efficient Federated Learning with Compensated Overlap-FedAvgIEEE Transactions on Parallel and Distributed Systems (TPDS), 2020 Yuhao Zhou Qing Ye Jiancheng Lv FedML 149 162 0 12 Dec 2020
Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective Jingwei Sun Ang Li Binghui Wang Huanrui Yang Hai Li Yiran Chen FedML 184 183 0 08 Dec 2020
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Jiabo He Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 403 446 0 07 Dec 2020
SSGD: A safe and efficient method of gradient descent Jinhuan Duan Xianxian Li Shiqi Gao Jinyan Wang Ziliang Zhong 71 4 0 03 Dec 2020
Privacy-preserving Collaborative Learning with Automatic Transformation SearchComputer Vision and Pattern Recognition (CVPR), 2020 Wei Gao Shangwei Guo Tianwei Zhang Han Qiu Yonggang Wen Yang Liu 193 56 0 25 Nov 2020
Minimal Model Structure Analysis for Input Reconstruction in Federated Learning Jia Qian Hiba Nassar Lars Kai Hansen FedML 100 9 0 29 Oct 2020
Exploring the Security Boundary of Data Reconstruction via Neuron Exclusivity AnalysisUSENIX Security Symposium (USENIX Security), 2020 Xudong Pan Mi Zhang Yifan Yan Jiaming Zhu Zhemin Yang AAML 143 24 0 26 Oct 2020
Layer-wise Characterization of Latent Information Leakage in Federated Learning Fan Mo Anastasia Borovykh Mohammad Malekzadeh Hamed Haddadi Soteris Demetriou FedML 111 34 0 17 Oct 2020
R-GAP: Recursive Gradient Attack on Privacy Junyi Zhu Matthew Blaschko FedML 213 146 0 15 Oct 2020
TextHide: Tackling Data Privacy in Language Understanding Tasks Yangsibo Huang Zhao Song Danqi Chen Keqin Li Sanjeev Arora FedML 95 59 0 12 Oct 2020
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous ClientsInternational Conference on Learning Representations (ICLR), 2020 Enmao Diao Jie Ding Vahid Tarokh FedML 316 630 0 03 Oct 2020
FedCVT: Semi-supervised Vertical Federated Learning with Cross-view Training Yan Kang Yang Liu Xinle Liang FedML 173 63 0 25 Aug 2020
LotteryFL: Personalized and Communication-Efficient Federated Learning with Lottery Ticket Hypothesis on Non-IID Datasets Ang Li Jingwei Sun Binghui Wang Lin Duan Sicheng Li Yiran Chen Xue Yang FedML 146 145 0 07 Aug 2020
FedBoosting: Federated Learning with Gradient Protected Boosting for Text RecognitionNeurocomputing (Neurocomputing), 2020 Hanchi Ren Jingjing Deng Xianghua Xie Xiaoke Ma Yi-Cheng Wang FedML 185 13 0 14 Jul 2020
Dataset Condensation with Gradient MatchingInternational Conference on Learning Representations (ICLR), 2020 Bo Zhao Konda Reddy Mopuri Hakan Bilen DD 354 582 0 10 Jun 2020
FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Data Xinwei Zhang Mingyi Hong S. Dhople W. Yin Yang Liu FedML 193 255 0 22 May 2020
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated LearningACM Transactions on Knowledge Discovery from Data (TKDD), 2020 Xinjian Luo Xiangqi Zhu FedML 410 29 0 27 Apr 2020
A Framework for Evaluating Gradient Leakage Attacks in Federated Learning Wenqi Wei Ling Liu Margaret Loper Ka-Ho Chow Mehmet Emre Gursoy Stacey Truex Yanzhao Wu FedML 127 157 0 22 Apr 2020
An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies David Enthoven Zaid Al-Ars FedML 113 56 0 01 Apr 2020
Inverting Gradients -- How easy is it to break privacy in federated learning?Neural Information Processing Systems (NeurIPS), 2020 Jonas Geiping Hartmut Bauermeister Hannah Dröge Michael Moeller FedML 415 1,407 0 31 Mar 2020
Threats to Federated Learning: A Survey Lingjuan Lyu Han Yu Qiang Yang FedML 406 493 0 04 Mar 2020
Learning to Prevent Leakage: Privacy-Preserving Inference in the Mobile Cloud Shuang Zhang Liyao Xiang Congcong Li Yixuan Wang Quanshi Zhang Zeyu Liu Yue Liu FedML 108 1 0 18 Dec 2019