iDLG: Improved Deep Leakage from Gradients

8 January 2020

Papers citing "iDLG: Improved Deep Leakage from Gradients"

50 / 334 papers shown

Title
Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage Zhuohang Li Jiaxin Zhang Lu Liu Jian-Dong Liu FedML 105 130 0 29 Mar 2022
Adaptive Aggregation For Federated Learning K.R. Jayaram Vinod Muthusamy Gegi Thomas Ashish Verma Mark Purcell FedML 130 20 0 23 Mar 2022
Federated Class-Incremental Learning Jiahua Dong Lixu Wang Zhen Fang Gan Sun Shichao Xu Tianlin Li Qi Zhu CLL FedML 162 209 0 22 Mar 2022
Closing the Generalization Gap of Cross-silo Federated Medical Image Segmentation An Xu Wenqi Li Pengfei Guo Dong Yang H. Roth Ali Hatamizadeh Can Zhao Daguang Xu Heng-Chiao Huang Ziyue Xu FedML 101 55 0 18 Mar 2022
No Free Lunch Theorem for Security and Utility in Federated Learning Xiaojin Zhang Hanlin Gu Lixin Fan Kai Chen Qiang Yang FedML 111 68 0 11 Mar 2022
Similarity-based Label Inference Attack against Training and Inference of Split Learning Junlin Liu Xinchen Lyu Qimei Cui Xiaofeng Tao FedML 109 32 0 10 Mar 2022
Beyond Gradients: Exploiting Adversarial Priors in Model Inversion Attacks Dmitrii Usynin Daniel Rueckert Georgios Kaissis SILM AAML 79 19 0 01 Mar 2022
Privacy Leakage of Adversarial Training Models in Federated Learning Systems Jingyang Zhang Yiran Chen Hai Helen Li FedML PICV 140 16 0 21 Feb 2022
LAMP: Extracting Text from Gradients with Language Model Priors Mislav Balunović Dimitar I. Dimitrov Nikola Jovanović Martin Vechev 103 66 0 17 Feb 2022
OLIVE: Oblivious Federated Learning on Trusted Execution Environment against the risk of sparsification Fumiyuki Kato Yang Cao Masatoshi Yoshikawa FedML 104 6 0 15 Feb 2022
Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data Shadi Rahimian Raouf Kerkouche I. Kurth Mario Fritz FedML 74 12 0 08 Feb 2022
Survey on Federated Learning Threats: concepts, taxonomy on attacks and defences, experimental study and challenges Nuria Rodríguez-Barroso Daniel Jiménez López M. V. Luzón Francisco Herrera Eugenio Martínez-Cámara FedML 117 246 0 20 Jan 2022
Get your Foes Fooled: Proximal Gradient Split Learning for Defense against Model Inversion Attacks on IoMT data Sunder Ali Khowaja I. Lee Kapal Dev M. Jarwar N. Qureshi AAML 120 19 0 12 Jan 2022
An Interpretable Federated Learning-based Network Intrusion Detection Framework Tian Dong Song Li Han Qiu Jialiang Lu FedML 67 17 0 10 Jan 2022
APRIL: Finding the Achilles' Heel on Privacy for Vision Transformers Jiahao Lu Xi Sheryl Zhang Tianli Zhao Xiangyu He Jian Cheng ViT PILM 80 26 0 28 Dec 2021
Gradient Leakage Attack Resilient Deep Learning Wenqi Wei Ling Liu SILM PILM AAML 94 52 0 25 Dec 2021
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey Shangwei Guo Xu Zhang Feiyu Yang Tianwei Zhang Yan Gan Tao Xiang Yang Liu FedML 119 12 0 19 Dec 2021
Batch Label Inference and Replacement Attacks in Black-Boxed Vertical Federated Learning Yang Liu Tianyuan Zou Yan Kang Wenhan Liu Yuanqin He Zhi-qian Yi Qian Yang FedML AAML 150 22 0 10 Dec 2021
Location Leakage in Federated Signal Maps Evita Bakopoulou Justin Ley Jiang Zhang Konstantinos Psounis A. Markopoulou FedML 103 5 0 07 Dec 2021
When the Curious Abandon Honesty: Federated Learning Is Not Private Franziska Boenisch Adam Dziedzic R. Schuster Ali Shahin Shamsabadi Ilia Shumailov Nicolas Papernot FedML AAML 172 201 0 06 Dec 2021
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning Yangsibo Huang Samyak Gupta Zhao Song Kai Li Sanjeev Arora FedML AAML SILM 111 301 0 30 Nov 2021
Understanding Training-Data Leakage from Gradients in Neural Networks for Image Classification Cangxiong Chen Neill D. F. Campbell FedML 81 26 0 19 Nov 2021
FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning Yuezhou Wu Yan Kang Jiahuan Luo Yuanqin He Qiang Yang FedML AAML 163 80 0 16 Nov 2021
Bayesian Framework for Gradient Leakage Mislav Balunović Dimitar I. Dimitrov Robin Staab Martin Vechev FedML 77 47 0 08 Nov 2021
Federated Learning Attacks Revisited: A Critical Discussion of Gaps, Assumptions, and Evaluation Setups A. Wainakh Ephraim Zimmer Sandeep Subedi Jens Keim Tim Grube Shankar Karuppayah Alejandro Sánchez Guinea Max Mühlhäuser 88 14 0 05 Nov 2021
Federated Split Vision Transformer for COVID-19 CXR Diagnosis using Task-Agnostic Training Sangjoon Park Gwanghyun Kim Jeongsol Kim Boah Kim Jong Chul Ye ViT FedML MedIm 126 32 0 02 Nov 2021
Revealing and Protecting Labels in Distributed Training Trung D. Q. Dang Om Thakkar Swaroop Indra Ramaswamy Rajiv Mathews Peter Chin Franccoise Beaufays 46 26 0 31 Oct 2021
Efficient passive membership inference attack in federated learning Oualid Zari Chuan Xu Giovanni Neglia FedML 92 36 0 31 Oct 2021
Dynamic Differential-Privacy Preserving SGD Jian Du Song Li Xiangyi Chen Siheng Chen Mingyi Hong 114 40 0 30 Oct 2021
Gradient Inversion with Generative Image Prior Jinwoo Jeon Jaechang Kim Kangwook Lee Sewoong Oh Jungseul Ok 91 168 0 28 Oct 2021
CAFE: Catastrophic Data Leakage in Vertical Federated Learning Xiao Jin Pin-Yu Chen Chia-Yi Hsu Chia-Mu Yu Tianyi Chen FedML 139 168 0 26 Oct 2021
Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models Liam H. Fowl Jonas Geiping W. Czaja Micah Goldblum Tom Goldstein FedML 165 157 0 25 Oct 2021
Towards General Deep Leakage in Federated Learning Jiahui Geng Yongli Mou Feifei Li Qing Li Oya Beyan Stefan Decker Chunming Rong FedML 97 61 0 18 Oct 2021
Federated Deep Learning with Bayesian Privacy Hanlin Gu Lixin Fan Bowen Li Jie Li Yan Kang Yuan Yao Qiang Yang FedML 175 23 0 27 Sep 2021
Dropout against Deep Leakage from Gradients Yanchong Zheng FedML 70 4 0 25 Aug 2021
Federated Learning for Privacy-Preserving Open Innovation Future on Digital Health Guodong Long Tao Shen Yue Tan Leah Gerrard Allison Clarke Jing Jiang FedML 106 48 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 86 93 0 20 Aug 2021
A Novel Attribute Reconstruction Attack in Federated Learning Lingjuan Lyu Chong Chen AAML 80 41 0 16 Aug 2021
Efficient Byzantine-Resilient Stochastic Gradient Desce Kaiyun Li Xiaojun Chen Ye Dong Peng Zhang Dakui Wang Shuai Zeng 40 0 0 15 Aug 2021
PRECODE - A Generic Model Extension to Prevent Deep Gradient Leakage Daniel Scheliga Patrick Mäder M. Seeland MIACV 99 38 0 10 Aug 2021
Privacy-Preserving Machine Learning: Methods, Challenges and Directions Runhua Xu Nathalie Baracaldo J. Joshi 100 113 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 Jiliang Tang FaML 252 226 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 95 25 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 82 2 0 05 Jul 2021
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy Xinwei Zhang Xiangyi Chen Min-Fong Hong Zhiwei Steven Wu Jinfeng Yi FedML 107 103 0 25 Jun 2021
Federated Learning on Non-IID Data: A Survey Hangyu Zhu Jinjin Xu Shiqing Liu Yaochu Jin OOD FedML 166 903 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 107 3 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 63 13 0 19 May 2021
User-Level Label Leakage from Gradients in Federated Learning A. Wainakh Fabrizio G. Ventola Till Müßig Jens Keim Carlos Garcia Cordero Ephraim Zimmer Tim Grube Kristian Kersting M. Mühlhäuser FedML AAML 76 56 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 75 9 0 17 May 2021