iDLG: Improved Deep Leakage from Gradients

8 January 2020

Papers citing "iDLG: Improved Deep Leakage from Gradients"

50 / 89 papers shown

Title
A Survey of Model Extraction Attacks and Defenses in Distributed Computing Environments Kaixiang Zhao Lincan Li Kaize Ding Neil Zhenqiang Gong Yue Zhao Yushun Dong AAML 49 0 0 22 Feb 2025
CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling Kaiyuan Zhang Siyuan Cheng Guangyu Shen Bruno Ribeiro Shengwei An Pin-Yu Chen X. Zhang Ninghui Li 100 1 0 28 Jan 2025
CYCle: Choosing Your Collaborators Wisely to Enhance Collaborative Fairness in Decentralized Learning Nurbek Tastan Samuel Horváth Karthik Nandakumar FedML 69 0 0 21 Jan 2025
Gradients Stand-in for Defending Deep Leakage in Federated Learning H. Yi H. Ren C. Hu Y. Li J. Deng Xin Xie FedML 30 0 0 11 Oct 2024
Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework Zilinghan Li Shilan He Ze Yang Minseok Ryu Kibaek Kim Ravi K. Madduri FedML 52 5 0 17 Sep 2024
Gradient Inversion of Federated Diffusion Models Jiyue Huang Chi Hong Lydia Y. Chen Stefanie Roos FedML 34 1 0 30 May 2024
DAGER: Exact Gradient Inversion for Large Language Models Ivo Petrov Dimitar I. Dimitrov Maximilian Baader Mark Niklas Muller Martin Vechev FedML 55 3 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 39 1 0 24 May 2024
On the Efficiency of Privacy Attacks in Federated Learning Nawrin Tabassum Ka-Ho Chow Xuyu Wang Wenbin Zhang Yanzhao Wu FedML 37 1 0 15 Apr 2024
You Can Use But Cannot Recognize: Preserving Visual Privacy in Deep Neural Networks Qiushi Li Yan Zhang Ju Ren Qi Li Yaoxue Zhang AAML PICV 41 23 0 05 Apr 2024
Federated Continual Learning via Knowledge Fusion: A Survey Xin Yang Hao Yu Xin Gao Hao Wang Junbo Zhang Tianrui Li FedML 30 31 0 27 Dec 2023
Enabling End-to-End Secure Federated Learning in Biomedical Research on Heterogeneous Computing Environments with APPFLx Trung-Hieu Hoang Jordan D. Fuhrman Ravi K. Madduri Miao Li Pranshu Chaturvedi ... Kibaek Kim Minseok Ryu Ryan Chard Eliu A. Huerta Maryellen L. Giger 24 5 0 14 Dec 2023
Privacy-preserving quantum federated learning via gradient hiding Changhao Li Niraj Kumar Zhixin Song Shouvanik Chakrabarti Marco Pistoia FedML 22 19 0 07 Dec 2023
A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective Xianghua Xie Chen Hu Hanchi Ren Jingjing Deng FedML AAML 40 19 0 27 Nov 2023
FLTrojan: Privacy Leakage Attacks against Federated Language Models Through Selective Weight Tampering Md. Rafi Ur Rashid Vishnu Asutosh Dasu Kang Gu Najrin Sultana Shagufta Mehnaz AAML FedML 44 10 0 24 Oct 2023
Text Embeddings Reveal (Almost) As Much As Text John X. Morris Volodymyr Kuleshov Vitaly Shmatikov Alexander M. Rush RALM 28 94 0 10 Oct 2023
Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception? Xiaoxiao Sun Nidham Gazagnadou Vivek Sharma Lingjuan Lyu Hongdong Li Liang Zheng 39 7 0 22 Sep 2023
Approximate and Weighted Data Reconstruction Attack in Federated Learning Yongcun Song Ziqi Wang Enrique Zuazua AAML FedML 22 4 0 13 Aug 2023
Feature Matching Data Synthesis for Non-IID Federated Learning Zijian Li Yuchang Sun Jiawei Shao Yuyi Mao Jessie Hui Wang Jun Zhang 26 20 0 09 Aug 2023
FLIPS: Federated Learning using Intelligent Participant Selection R. Bhope K. R. Jayaram N. Venkatasubramanian Ashish Verma Gegi Thomas FedML 29 3 0 07 Aug 2023
Compressed Private Aggregation for Scalable and Robust Federated Learning over Massive Networks Natalie Lang Nir Shlezinger Rafael G. L. DÓliveira S. E. Rouayheb FedML 70 4 0 01 Aug 2023
Samplable Anonymous Aggregation for Private Federated Data Analysis Kunal Talwar Shan Wang Audra McMillan Vojta Jina Vitaly Feldman ... Congzheng Song Karl Tarbe Sebastian Vogt L. Winstrom Shundong Zhou FedML 38 13 0 27 Jul 2023
Mitigating Cross-client GANs-based Attack in Federated Learning Hong Huang Xinyu Lei Tao Xiang AAML 50 1 0 25 Jul 2023
A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency Jiawei Shao Zijian Li Wenqiang Sun Tailin Zhou Yuchang Sun Lumin Liu Zehong Lin Yuyi Mao Jun Zhang FedML 43 23 0 20 Jul 2023
FheFL: Fully Homomorphic Encryption Friendly Privacy-Preserving Federated Learning with Byzantine Users Y. Rahulamathavan Charuka Herath Xiaolan Liu S. Lambotharan Carsten Maple 25 12 0 08 Jun 2023
Avoid Adversarial Adaption in Federated Learning by Multi-Metric Investigations T. Krauß Alexandra Dmitrienko AAML 22 4 0 06 Jun 2023
Theoretically Principled Federated Learning for Balancing Privacy and Utility Xiaojin Zhang Wenjie Li Kai Chen Shutao Xia Qian Yang FedML 19 9 0 24 May 2023
Gradient Leakage Defense with Key-Lock Module for Federated Learning Hanchi Ren Jingjing Deng Xianghua Xie Xiaoke Ma J. Ma FedML 24 2 0 06 May 2023
A Game-theoretic Framework for Privacy-preserving Federated Learning Xiaojin Zhang Lixin Fan Si-Yi Wang Wenjie Li Kai Chen Qiang Yang FedML 21 4 0 11 Apr 2023
RecUP-FL: Reconciling Utility and Privacy in Federated Learning via User-configurable Privacy Defense Yue-li Cui Syed Imran Ali Meerza Zhuohang Li Luyang Liu Jiaxin Zhang Jian-Dong Liu AAML FedML 21 4 0 11 Apr 2023
Robust and IP-Protecting Vertical Federated Learning against Unexpected Quitting of Parties Jingwei Sun Zhixu Du Anna Dai Saleh Baghersalimi Alireza Amirshahi David Atienza Yiran Chen FedML 11 7 0 28 Mar 2023
The Resource Problem of Using Linear Layer Leakage Attack in Federated Learning Joshua C. Zhao A. Elkordy Atul Sharma Yahya H. Ezzeldin A. Avestimehr S. Bagchi FedML 37 12 0 27 Mar 2023
Personalized Privacy-Preserving Framework for Cross-Silo Federated Learning Van Tuan Tran Huy Hieu Pham Kok-Seng Wong FedML 33 7 0 22 Feb 2023
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy Yifei Zhang Dun Zeng Jinglong Luo Zenglin Xu Irwin King FedML 84 47 0 21 Feb 2023
Personalized and privacy-preserving federated heterogeneous medical image analysis with PPPML-HMI Juexiao Zhou Longxi Zhou Di Wang Xiaopeng Xu Haoyang Li Yuetan Chu Wenkai Han Xin Gao 17 20 0 20 Feb 2023
Bounding Training Data Reconstruction in DP-SGD Jamie Hayes Saeed Mahloujifar Borja Balle AAML FedML 33 39 0 14 Feb 2023
Mutual Information Regularization for Vertical Federated Learning Tianyuan Zou Yang Liu Ya-Qin Zhang AAML FedML 27 7 0 01 Jan 2023
Reconstructing Training Data from Model Gradient, Provably Zihan Wang Jason D. Lee Qi Lei FedML 22 24 0 07 Dec 2022
Refiner: Data Refining against Gradient Leakage Attacks in Federated Learning Mingyuan Fan Cen Chen Chengyu Wang Ximeng Liu Wenmeng Zhou Jun Huang AAML FedML 34 0 0 05 Dec 2022
Federated Learning Attacks and Defenses: A Survey Yao Chen Yijie Gui Hong Lin Wensheng Gan Yongdong Wu FedML 38 29 0 27 Nov 2022
Optimal Privacy Preserving for Federated Learning in Mobile Edge Computing Hai M. Nguyen N. Chu Diep N. Nguyen D. Hoang Van-Dinh Nguyen Minh Hoàng Hà E. Dutkiewicz Marwan Krunz FedML 19 1 0 14 Nov 2022
Two Models are Better than One: Federated Learning Is Not Private For Google GBoard Next Word Prediction Mohamed Suliman D. Leith SILM FedML 23 7 0 30 Oct 2022
Local Model Reconstruction Attacks in Federated Learning and their Uses Ilias Driouich Chuan Xu Giovanni Neglia F. Giroire Eoin Thomas AAML FedML 29 2 0 28 Oct 2022
Analysing Training-Data Leakage from Gradients through Linear Systems and Gradient Matching Cangxiong Chen Neill D. F. Campbell FedML 24 1 0 20 Oct 2022
Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability Zhao-quan Song Yitan Wang Zheng Yu Licheng Zhang FedML 23 28 0 15 Oct 2022
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning using Independent Component Analysis Sanjay Kariyappa Chuan Guo Kiwan Maeng Wenjie Xiong G. E. Suh Moinuddin K. Qureshi Hsien-Hsin S. Lee FedML 13 29 0 12 Sep 2022
Exploring Semantic Attributes from A Foundation Model for Federated Learning of Disjoint Label Spaces Shitong Sun Chenyang Si Guile Wu S. Gong FedML 23 0 0 29 Aug 2022
Joint Privacy Enhancement and Quantization in Federated Learning Natalie Lang Elad Sofer Tomer Shaked Nir Shlezinger FedML 32 46 0 23 Aug 2022
Dropout is NOT All You Need to Prevent Gradient Leakage Daniel Scheliga Patrick Mäder M. Seeland FedML 22 12 0 12 Aug 2022
ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production Scale Gopinath Chennupati Milind Rao Gurpreet Chadha Aaron Eakin A. Raju ... Andrew Oberlin Buddha Nandanoor Prahalad Venkataramanan Zheng Wu Pankaj Sitpure CLL 22 8 0 19 Jul 2022