iDLG: Improved Deep Leakage from Gradients

8 January 2020

Papers citing "iDLG: Improved Deep Leakage from Gradients"

50 / 111 papers shown

Title
Mixed Precision Quantization to Tackle Gradient Leakage Attacks in Federated Learning Pretom Roy Ovi Emon Dey Nirmalya Roy A. Gangopadhyay FedML 26 4 0 22 Oct 2022
Analysing Training-Data Leakage from Gradients through Linear Systems and Gradient Matching Cangxiong Chen Neill D. F. Campbell FedML 37 1 0 20 Oct 2022
Learning to Invert: Simple Adaptive Attacks for Gradient Inversion in Federated Learning Ruihan Wu Xiangyu Chen Chuan Guo Kilian Q. Weinberger FedML 20 26 0 19 Oct 2022
Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability Zhao Song Yitan Wang Zheng Yu Licheng Zhang FedML 23 28 0 15 Oct 2022
CrowdGuard: Federated Backdoor Detection in Federated Learning Phillip Rieger T. Krauß Markus Miettinen Alexandra Dmitrienko Ahmad-Reza Sadeghi Technical University Darmstadt AAML FedML 32 22 0 14 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 29 29 0 12 Sep 2022
A Framework for Evaluating Privacy-Utility Trade-off in Vertical Federated Learning Yan Kang Jiahuan Luo Yuanqin He Xiaojin Zhang Lixin Fan Qiang Yang FedML 19 15 0 08 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 30 0 0 29 Aug 2022
Joint Privacy Enhancement and Quantization in Federated Learning Natalie Lang Elad Sofer Tomer Shaked Nir Shlezinger FedML 39 46 0 23 Aug 2022
Dropout is NOT All You Need to Prevent Gradient Leakage Daniel Scheliga Patrick Mäder M. Seeland FedML 44 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 27 8 0 19 Jul 2022
Enhanced Security and Privacy via Fragmented Federated Learning N. Jebreel J. Domingo-Ferrer Alberto Blanco-Justicia David Sánchez FedML 39 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 38 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 35 36 0 15 Jun 2022
Deep Leakage from Model in Federated Learning Zihao Zhao Mengen Luo Wenbo Ding FedML 26 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 36 46 0 08 Jun 2022
Encoded Gradients Aggregation against Gradient Leakage in Federated Learning Dun Zeng Shiyu Liu Siqi Liang Zonghang Li Hongya Wang Irwin King Zenglin Xu FedML 34 0 0 26 May 2022
Recovering Private Text in Federated Learning of Language Models Samyak Gupta Yangsibo Huang Zexuan Zhong Tianyu Gao Kai Li Danqi Chen FedML 40 75 0 17 May 2022
AGIC: Approximate Gradient Inversion Attack on Federated Learning Jin Xu Chi Hong Jiyue Huang L. Chen Jérémie Decouchant AAML FedML 37 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 38 2 0 25 Apr 2022
FederatedScope: A Flexible Federated Learning Platform for Heterogeneity Yuexiang Xie Zhen Wang Dawei Gao Daoyuan Chen Liuyi Yao Weirui Kuang Yaliang Li Bolin Ding Jingren Zhou FedML 34 88 0 11 Apr 2022
Multi-Task Distributed Learning using Vision Transformer with Random Patch Permutation Sangjoon Park Jong Chul Ye FedML MedIm 47 19 0 07 Apr 2022
Adaptive Aggregation For Federated Learning K.R. Jayaram Vinod Muthusamy Gegi Thomas Ashish Verma Mark Purcell FedML 33 16 0 23 Mar 2022
Federated Class-Incremental Learning Jiahua Dong Lixu Wang Zhen Fang Gan Sun Shichao Xu Tianlin Li Qi Zhu CLL FedML 38 169 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 38 52 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 24 64 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 35 26 0 10 Mar 2022
Privacy Leakage of Adversarial Training Models in Federated Learning Systems Jingyang Zhang Yiran Chen Hai Helen Li FedML PICV 37 15 0 21 Feb 2022
LAMP: Extracting Text from Gradients with Language Model Priors Mislav Balunović Dimitar I. Dimitrov Nikola Jovanović Martin Vechev 27 57 0 17 Feb 2022
Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data Shadi Rahimian Raouf Kerkouche I. Kurth Mario Fritz FedML 22 11 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 37 213 0 20 Jan 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 32 48 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 31 9 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 19 19 0 10 Dec 2021
Location Leakage in Federated Signal Maps Evita Bakopoulou Justin Ley Jiang Zhang Konstantinos Psounis A. Markopoulou FedML 22 5 0 07 Dec 2021
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning Yangsibo Huang Samyak Gupta Zhao Song Kai Li Sanjeev Arora FedML AAML SILM 31 269 0 30 Nov 2021
Understanding Training-Data Leakage from Gradients in Neural Networks for Image Classification Cangxiong Chen Neill D. F. Campbell FedML 22 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 69 0 16 Nov 2021
Bayesian Framework for Gradient Leakage Mislav Balunović Dimitar I. Dimitrov Robin Staab Martin Vechev FedML 27 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 38 145 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 30 55 0 18 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 79 0 20 Aug 2021
Privacy-Preserving Machine Learning: Methods, Challenges and Directions Runhua Xu Nathalie Baracaldo J. Joshi 32 99 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 104 197 0 12 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 32 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 56 244 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 25 462 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 27 19 0 08 Jan 2021
Fidel: Reconstructing Private Training Samples from Weight Updates in Federated Learning David Enthoven Zaid Al-Ars FedML 62 14 0 01 Jan 2021