iDLG: Improved Deep Leakage from Gradients

8 January 2020

Papers citing "iDLG: Improved Deep Leakage from Gradients"

50 / 349 papers shown

Title
Membership Inference Attacks and Defenses in Federated Learning: A SurveyACM Computing Surveys (ACM CSUR), 2024 Li Bai Haibo Hu Qingqing Ye Haoyang Li Leixia Wang Jianliang Xu FedML 193 44 0 09 Dec 2024
Privacy-Preserving Federated Learning via Homomorphic Adversarial Networks Wenhan Dong Chao Lin Xinlei He Xinyi Huang Shengmin Xu PICV 215 0 0 02 Dec 2024
Gradient Inversion Attack on Graph Neural Networks Divya Anand Sinha Ruijie Du Yezi Liu Athina Markopolou Yanning Shen FedML 192 3 0 29 Nov 2024
Optimal Defenses Against Gradient Reconstruction Attacks Yuxiao Chen Gamze Gürsoy Qi Lei FedML AAML 170 1 0 06 Nov 2024
NeurIPS 2023 Competition: Privacy Preserving Federated Learning Document VQA Marlon Tobaben Mohamed Ali Souibgui Rubèn Pérez Tito Khanh Nguyen Raouf Kerkouche ... Josep Lladós Ernest Valveny Antti Honkela Mario Fritz Dimosthenis Karatzas FedML 225 1 0 06 Nov 2024
Gradient-Guided Conditional Diffusion Models for Private Image Reconstruction: Analyzing Adversarial Impacts of Differential Privacy and Denoising Tao Huang Jiayang Meng Hong Chen Guolong Zheng Xu Yang Xun Yi Hua Wang DiffM 118 3 0 05 Nov 2024
FEDLAD: Federated Evaluation of Deep Leakage Attacks and Defenses Isaac Baglin Xiatian Zhu Simon Hadfield FedML 156 1 0 05 Nov 2024
Federated Black-Box Adaptation for Semantic SegmentationNeural Information Processing Systems (NeurIPS), 2024 Jay N. Paranjape S. Sikder S. Vedula Vishal M. Patel FedML 145 1 0 31 Oct 2024
Extracting Spatiotemporal Data from Gradients with Large Language Models Lele Zheng Yang Cao Renhe Jiang Kenjiro Taura Yulong Shen Sheng Li Masatoshi Yoshikawa 117 1 0 21 Oct 2024
Investigating Effective Speaker Property Privacy Protection in Federated Learning for Speech Emotion RecognitionACM Multimedia Asia (MMAsia), 2024 Chao Tan Sheng Li Yang Cao Zhao Ren Tanja Schultz 109 0 0 17 Oct 2024
Gradients Stand-in for Defending Deep Leakage in Federated Learning H. Yi H. Ren C. Hu Y. Li J. Deng Xin Xie FedML 108 0 0 11 Oct 2024
SoK: Towards Security and Safety of Edge AI Tatjana Wingarz Anne Lauscher Janick Edinger Dominik Kaaser Stefan Schulte Mathias Fischer 166 0 0 07 Oct 2024
Federated Learning Nodes Can Reconstruct Peers' Image Data Ethan Wilson Kai Yue Chau-Wai Wong H. Dai FedML 165 1 0 07 Oct 2024
Advances in Privacy Preserving Federated Learning to Realize a Truly Learning Healthcare SystemInternational Conference on Trust, Privacy and Security in Intelligent Systems and Applications (ICPSISA), 2024 Ravi K. Madduri Zilinghan Li Tarak Nandi Kibaek Kim Minseok Ryu Alex Rodriguez 109 3 0 29 Sep 2024
Subject Data Auditing via Source Inference Attack in Cross-Silo Federated LearningJournal of Information Security and Applications (JISA), 2024 Jiaxin Li Marco Arazzi Antonino Nocera Mauro Conti 105 3 0 28 Sep 2024
Privacy Attack in Federated Learning is Not Easy: An Experimental Study Hangyu Zhu Liyuan Huang Zhenping Xie FedML 125 1 0 28 Sep 2024
In-depth Analysis of Privacy Threats in Federated Learning for Medical Data B. Das M. H. Amini Yanzhao Wu 109 1 0 27 Sep 2024
Federated Learning under Attack: Improving Gradient Inversion for Batch of Images Luiz Leite Yuri Santo Bruno L. Dalmazo André Riker FedML 48 6 0 26 Sep 2024
Perfect Gradient Inversion in Federated Learning: A New Paradigm from the Hidden Subset Sum Problem Qiongxiu Li Lixia Luo Agnese Gini Changlong Ji Zhanhao Hu Xiao-Li Li Chengfang Fang Jie Shi Xiaolin Hu FedML 123 4 0 21 Sep 2024
Data Poisoning and Leakage Analysis in Federated Learning Wenqi Wei Tiansheng Huang Zachary Yahn Anoop Singhal Margaret Loper Ling Liu FedML SILM 112 0 0 19 Sep 2024
Advances in APPFL: A Comprehensive and Extensible Federated Learning FrameworkIEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid), 2024 Zilinghan Li Shilan He Ze Yang Minseok Ryu Kibaek Kim Ravi K. Madduri FedML 257 19 0 17 Sep 2024
Exploring User-level Gradient Inversion with a Diffusion Prior Zhuohang Li Andrew Lowy Jing Liu T. Koike-Akino Bradley Malin K. Parsons Ye Wang DiffM 103 1 0 11 Sep 2024
$S^2$ NeRF: Privacy-preserving Training Framework for NeRFConference on Computer and Communications Security (CCS), 2024 Bokang Zhang Yanglin Zhang Zhikun Zhang Jinglan Yang Lingying Huang Junfeng Wu 163 2 0 03 Sep 2024
DAMe: Personalized Federated Social Event Detection with Dual Aggregation MechanismInternational Conference on Information and Knowledge Management (CIKM), 2024 Xiaoyan Yu Yifan Wei Pu Li Shuaishuai Zhou Hao Peng Li Sun Liehuang Zhu Philip S. Yu FedML 166 2 0 01 Sep 2024
Understanding Data Reconstruction Leakage in Federated Learning from a Theoretical Perspective Zifan Wang Binghui Zhang Meng Pang Yuan Hong Binghui Wang FedML 144 0 0 22 Aug 2024
Random Gradient Masking as a Defensive Measure to Deep Leakage in Federated Learning Joon Kim Sejin Park AAML FedML 151 2 0 15 Aug 2024
Efficient Byzantine-Robust and Provably Privacy-Preserving Federated Learning Chenfei Nie Qiang Li Yuxin Yang Yuede Ji Binghui Wang 148 1 0 29 Jul 2024
MedLeak: Multimodal Medical Data Leakage in Secure Federated Learning with Crafted Models Shanghao Shi Md Shahedul Haque Abhijeet Parida Chaoyu Zhang M. Linguraru Y. T. Hou Syed Muhammad Anwar W. Lou FedML 146 4 0 13 Jul 2024
Provable Privacy Advantages of Decentralized Federated Learning via Distributed Optimization Wenrui Yu Qiongxiu Li Milan Lopuhaä-Zwakenberg Mads Græsbøll Christensen Richard Heusdens FedML 104 7 0 12 Jul 2024
Enhancing Privacy of Spatiotemporal Federated Learning against Gradient Inversion Attacks Lele Zheng Yang Cao Renhe Jiang Kenjiro Taura Yulong Shen Sheng Li Masatoshi Yoshikawa AAML 138 3 0 11 Jul 2024
QBI: Quantile-based Bias Initialization for Efficient Private Data Reconstruction in Federated Learning Micha V. Nowak Tim P. Bott David Khachaturov Frank Puppe Adrian Krenzer Amar Hekalo FedML 101 1 0 26 Jun 2024
Machine Unlearning with Minimal Gradient Dependence for High Unlearning Ratios Tao Huang Ziyang Chen Jiayang Meng Qingyu Huang Xu Yang Xun Yi Ibrahim Khalil MU 102 0 0 24 Jun 2024
Breaking Secure Aggregation: Label Leakage from Aggregated Gradients in Federated Learning Peng Kuang Zhiwei Chang Jiahui Hu Xiaoyi Pang Jiacheng Du Yongle Chen Kui Ren FedML 115 7 0 22 Jun 2024
Linkage on Security, Privacy and Fairness in Federated Learning: New Balances and New Perspectives Linlin Wang Tianqing Zhu Wanlei Zhou Philip S. Yu 123 3 0 16 Jun 2024
Knowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions Laiqiao Qin Tianqing Zhu Wanlei Zhou Philip S. Yu 143 9 0 16 Jun 2024
Is Diffusion Model Safe? Severe Data Leakage via Gradient-Guided Diffusion Model Jiayang Meng Tao Huang Hong Chen Cuiping Li DiffM 98 1 0 13 Jun 2024
R-CONV: An Analytical Approach for Efficient Data Reconstruction via Convolutional GradientsWISE (WISE), 2024 T. Eltaras Q. Malluhi Alessandro Savino S. Di Carlo Adnan Qayyum Junaid Qadir FedML 87 3 0 06 Jun 2024
Inference Attacks: A Taxonomy, Survey, and Promising Directions Feng Wu Lei Cui Shaowen Yao Shui Yu 256 2 0 04 Jun 2024
No Vandalism: Privacy-Preserving and Byzantine-Robust Federated Learning Zhibo Xing Zijian Zhang Ziáng Zhang Jiamou Liu Liehuang Zhu Giovanni Russello FedML 130 3 0 03 Jun 2024
Seeing the Forest through the Trees: Data Leakage from Partial Transformer Gradients Weijun Li Xingliang Yuan Mark Dras PILM 136 4 0 03 Jun 2024
Amalgam: A Framework for Obfuscated Neural Network Training on the Cloud Sifat Ut Taki Spyridon Mastorakis FedML 140 1 0 02 Jun 2024
Gradient Inversion of Federated Diffusion Models Jiyue Huang Chi Hong Lydia Y. Chen Stefanie Roos FedML 122 2 0 30 May 2024
Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable Martín Bertrán Shuai Tang Michael Kearns Jamie Morgenstern Aaron Roth Zhiwei Steven Wu AAML 143 20 0 30 May 2024
Enhancing Security and Privacy in Federated Learning using Low-Dimensional Update Representation and Proximity-Based Defense Wenjie Li K. Fan Jingyuan Zhang Hui Li Wei Yang Bryan Lim Qiang Yang AAML FedML 135 1 0 29 May 2024
DAGER: Exact Gradient Inversion for Large Language Models Ivo Petrov Dimitar I. Dimitrov Maximilian Baader Mark Niklas Muller Martin Vechev FedML 137 9 0 24 May 2024
Leakage-Resilient and Carbon-Neutral Aggregation Featuring the Federated AI-enabled Critical Infrastructure Zehang Deng Ruoxi Sun Minhui Xue Sheng Wen S. Çamtepe Surya Nepal Yang Xiang 123 6 0 24 May 2024
Federated Learning in Healthcare: Model Misconducts, Security, Challenges, Applications, and Future Research Directions -- A Systematic Review Md. Shahin Ali M. Ahsan Lamia Tasnim Sadia Afrin Koushik Biswas Maruf Md. Sajjad Hossain Md Mahfuz Ahmed Ronok Hashan Md. Khairul Islam Shivakumar Raman 118 16 0 22 May 2024
Information Leakage from Embedding in Large Language Models Zhipeng Wan Anda Cheng Yinggui Wang Lei Wang PILM 133 5 0 20 May 2024
Dealing Doubt: Unveiling Threat Models in Gradient Inversion Attacks under Federated Learning, A Survey and Taxonomy Yichuan Shi Olivera Kotevska Viktor Reshniak Abhishek Singh Ramesh Raskar AAML 96 3 0 16 May 2024
Feature-based Federated Transfer Learning: Communication Efficiency, Robustness and PrivacyIEEE Transactions on Machine Learning in Communications and Networking (IEEE TMLCN), 2024 Feng Wang M. C. Gursoy Senem Velipasalar 151 3 0 15 May 2024