iDLG: Improved Deep Leakage from Gradients

8 January 2020

Papers citing "iDLG: Improved Deep Leakage from Gradients"

39 / 89 papers shown

Title
Enhanced Security and Privacy via Fragmented Federated Learning N. Jebreel J. Domingo-Ferrer Alberto Blanco-Justicia David Sánchez FedML 26 26 0 13 Jul 2022
An Efficient Industrial Federated Learning Framework for AIoT: A Face Recognition Application Youlong Ding Xueyang Wu Zhitao Li Zeheng Wu S. Tan Qian Xu Weike Pan Qiang Yang FedML 33 4 0 21 Jun 2022
A Survey on Gradient Inversion: Attacks, Defenses and Future Directions Rui Zhang Song Guo Junxiao Wang Xin Xie Dacheng Tao 27 36 0 15 Jun 2022
Deep Leakage from Model in Federated Learning Zihao Zhao Mengen Luo Wenbo Ding FedML 18 14 0 10 Jun 2022
Gradient Obfuscation Gives a False Sense of Security in Federated Learning Kai Yue Richeng Jin Chau-Wai Wong D. Baron H. Dai FedML 28 46 0 08 Jun 2022
Recovering Private Text in Federated Learning of Language Models Samyak Gupta Yangsibo Huang Zexuan Zhong Tianyu Gao Kai Li Danqi Chen FedML 27 74 0 17 May 2022
AGIC: Approximate Gradient Inversion Attack on Federated Learning Jin Xu Chi Hong Jiyue Huang L. Chen Jérémie Decouchant AAML FedML 19 21 0 28 Apr 2022
Analysing the Influence of Attack Configurations on the Reconstruction of Medical Images in Federated Learning M. Dahlgaard Morten Wehlast Jorgensen N. Fuglsang Hiba Nassar FedML AAML 33 2 0 25 Apr 2022
Multi-Task Distributed Learning using Vision Transformer with Random Patch Permutation Sangjoon Park Jong Chul Ye FedML MedIm 42 19 0 07 Apr 2022
Adaptive Aggregation For Federated Learning K. R. Jayaram Vinod Muthusamy Gegi Thomas Ashish Verma Mark Purcell FedML 25 16 0 23 Mar 2022
Federated Class-Incremental Learning Jiahua Dong Lixu Wang Zhen Fang Gan Sun Shichao Xu Xiao Wang Qi Zhu CLL FedML 24 168 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 33 51 0 18 Mar 2022
Similarity-based Label Inference Attack against Training and Inference of Split Learning Junlin Liu Xinchen Lyu Qimei Cui Xiaofeng Tao FedML 24 26 0 10 Mar 2022
Privacy Leakage of Adversarial Training Models in Federated Learning Systems Jingyang Zhang Yiran Chen Hai Helen Li FedML PICV 27 15 0 21 Feb 2022
Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data Shadi Rahimian Raouf Kerkouche I. Kurth Mario Fritz FedML 14 11 0 08 Feb 2022
An Interpretable Federated Learning-based Network Intrusion Detection Framework Tian Dong Song Li Han Qiu Jialiang Lu FedML 14 16 0 10 Jan 2022
Gradient Leakage Attack Resilient Deep Learning Wenqi Wei Ling Liu SILM PILM AAML 22 46 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 28 9 0 19 Dec 2021
Location Leakage in Federated Signal Maps Evita Bakopoulou Justin Ley Jiang Zhang Konstantinos Psounis A. Markopoulou FedML 20 5 0 07 Dec 2021
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning Yangsibo Huang Samyak Gupta Zhao-quan Song Kai Li Sanjeev Arora FedML AAML SILM 12 269 0 30 Nov 2021
Understanding Training-Data Leakage from Gradients in Neural Networks for Image Classification Cangxiong Chen Neill D. F. Campbell FedML 9 24 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 19 68 0 16 Nov 2021
Bayesian Framework for Gradient Leakage Mislav Balunović Dimitar I. Dimitrov Robin Staab Martin Vechev FedML 19 41 0 08 Nov 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 32 145 0 25 Oct 2021
UnSplit: Data-Oblivious Model Inversion, Model Stealing, and Label Inference Attacks Against Split Learning Ege Erdogan Alptekin Kupcu A. E. Cicek FedML MIACV 35 77 0 20 Aug 2021
Privacy-Preserving Machine Learning: Methods, Challenges and Directions Runhua Xu Nathalie Baracaldo J. Joshi 24 100 0 10 Aug 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 22 91 0 25 Jun 2021
From Distributed Machine Learning to Federated Learning: A Survey Ji Liu Jizhou Huang Yang Zhou Xuhong Li Shilei Ji Haoyi Xiong Dejing Dou FedML OOD 51 243 0 29 Apr 2021
See through Gradients: Image Batch Recovery via GradInversion Hongxu Yin Arun Mallya Arash Vahdat J. Álvarez Jan Kautz Pavlo Molchanov FedML 25 460 0 15 Apr 2021
Differentially Private Federated Learning for Cancer Prediction C. Béguier Jean Ogier du Terrail I. Meah M. Andreux Eric W. Tramel FedML 19 19 0 08 Jan 2021
Fidel: Reconstructing Private Training Samples from Weight Updates in Federated Learning David Enthoven Zaid Al-Ars FedML 55 14 0 01 Jan 2021
Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective Jingwei Sun Ang Li Binghui Wang Huanrui Yang Hai Li Yiran Chen FedML 19 163 0 08 Dec 2020
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 183 355 0 07 Dec 2020
R-GAP: Recursive Gradient Attack on Privacy Junyi Zhu Matthew Blaschko FedML 6 132 0 15 Oct 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 H. Li FedML 6 125 0 07 Aug 2020
Dataset Condensation with Gradient Matching Bo-Lu Zhao Konda Reddy Mopuri Hakan Bilen DD 36 472 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 21 227 0 22 May 2020
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning Xinjian Luo Xiangqi Zhu FedML 73 25 0 27 Apr 2020
An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies David Enthoven Zaid Al-Ars FedML 57 50 0 01 Apr 2020