Papers citing 'iDLG: Improved Deep Leakage from Gradients'

Title
Deep Leakage from Model in Federated Learning Zihao Zhao Mengen Luo Wenbo Ding FedML 85 17 0 10 Jun 2022
Gradient Obfuscation Gives a False Sense of Security in Federated LearningUSENIX Security Symposium (USENIX Security), 2022 Kai Yue Richeng Jin Chau-Wai Wong D. Baron H. Dai FedML 165 63 0 08 Jun 2022
THE-X: Privacy-Preserving Transformer Inference with Homomorphic EncryptionFindings (Findings), 2022 Tianyu Chen Hangbo Bao Shaohan Huang Li Dong Binxing Jiao Daxin Jiang Haoyi Zhou Jianxin Li Furu Wei 203 123 0 01 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 113 0 0 26 May 2022
Incentivizing Federated Learning Shuyu Kong You Li Hai Zhou FedML 157 8 0 22 May 2022
BlockDFL: A Blockchain-based Fully Decentralized Peer-to-Peer Federated Learning FrameworkThe Web Conference (WWW), 2022 Zhen Qin Xueqiang Yan Mengchu Zhou Shuiguang Deng 135 28 0 21 May 2022
Recovering Private Text in Federated Learning of Language ModelsNeural Information Processing Systems (NeurIPS), 2022 Samyak Gupta Yangsibo Huang Zexuan Zhong Tianyu Gao Kai Li Danqi Chen FedML 171 90 0 17 May 2022
Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-Ray DataItalian National Conference on Sensors (INS), 2022 Joceline Ziegler Bjarne Pfitzner H. Schulz A. Saalbach B. Arnrich FedML 89 20 0 06 May 2022
AGIC: Approximate Gradient Inversion Attack on Federated LearningIEEE International Symposium on Reliable Distributed Systems (SRDS), 2022 Jin Xu Chi Hong Jiyue Huang L. Chen Jérémie Decouchant AAML FedML 172 27 0 28 Apr 2022
Enhancing Privacy against Inversion Attacks in Federated Learning by using Mixing Gradients Strategies Shaltiel Eloul Fran Silavong Sanket Kamthe Antonios Georgiadis Sean J. Moran FedML 72 7 0 26 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 128 3 0 25 Apr 2022
FederatedScope: A Flexible Federated Learning Platform for HeterogeneityProceedings of the VLDB Endowment (PVLDB), 2022 Yuexiang Xie Zhen Wang Dawei Gao Daoyuan Chen Liuyi Yao Weirui Kuang Yaliang Li Bolin Ding Jingren Zhou FedML 255 103 0 11 Apr 2022
Multi-Task Distributed Learning using Vision Transformer with Random Patch PermutationIEEE Transactions on Medical Imaging (IEEE TMI), 2022 Sangjoon Park Jong Chul Ye FedML MedIm 150 22 0 07 Apr 2022
DeFTA: A Plug-and-Play Decentralized Replacement for FedAvg Yuhao Zhou M. Shi Yuxin Tian Qing Ye Jiancheng Lv FedML 73 2 0 06 Apr 2022
Perfectly Accurate Membership Inference by a Dishonest Central Server in Federated LearningIEEE Transactions on Dependable and Secure Computing (TDSC), 2022 Georg Pichler Marco Romanelli L. Rey Vega Pablo Piantanida FedML 102 11 0 30 Mar 2022
Auditing Privacy Defenses in Federated Learning via Generative Gradient LeakageComputer Vision and Pattern Recognition (CVPR), 2022 Zhuohang Li Jiaxin Zhang Lu Liu Jian-Dong Liu FedML 161 142 0 29 Mar 2022
Adaptive Aggregation For Federated Learning K.R. Jayaram Vinod Muthusamy Gegi Thomas Ashish Verma Mark Purcell FedML 170 20 0 23 Mar 2022
Federated Class-Incremental LearningComputer Vision and Pattern Recognition (CVPR), 2022 Jiahua Dong Lixu Wang Zhen Fang Gan Sun Shichao Xu Tianlin Li Qi Zhu CLL FedML 214 229 0 22 Mar 2022
Closing the Generalization Gap of Cross-silo Federated Medical Image SegmentationComputer Vision and Pattern Recognition (CVPR), 2022 An Xu Wenqi Li Pengfei Guo Dong Yang H. Roth Ali Hatamizadeh Can Zhao Daguang Xu Heng-Chiao Huang Ziyue Xu FedML 113 63 0 18 Mar 2022
No Free Lunch Theorem for Security and Utility in Federated LearningACM Transactions on Intelligent Systems and Technology (ACM TIST), 2022 Xiaojin Zhang Hanlin Gu Lixin Fan Kai Chen Qiang Yang FedML 131 73 0 11 Mar 2022
Similarity-based Label Inference Attack against Training and Inference of Split LearningIEEE Transactions on Information Forensics and Security (IEEE TIFS), 2022 Junlin Liu Xinchen Lyu Qimei Cui Xiaofeng Tao FedML 125 32 0 10 Mar 2022
Beyond Gradients: Exploiting Adversarial Priors in Model Inversion AttacksACM Transactions on Privacy and Security (TOPS), 2022 Dmitrii Usynin Daniel Rueckert Georgios Kaissis SILM AAML 95 23 0 01 Mar 2022
Privacy Leakage of Adversarial Training Models in Federated Learning Systems Jingyang Zhang Yiran Chen Hai Helen Li FedML PICV 156 16 0 21 Feb 2022
LAMP: Extracting Text from Gradients with Language Model PriorsNeural Information Processing Systems (NeurIPS), 2022 Mislav Balunović Dimitar I. Dimitrov Nikola Jovanović Martin Vechev 132 73 0 17 Feb 2022
OLIVE: Oblivious Federated Learning on Trusted Execution Environment against the risk of sparsificationProceedings of the VLDB Endowment (PVLDB), 2022 Fumiyuki Kato Yang Cao Masatoshi Yoshikawa FedML 144 6 0 15 Feb 2022
Practical Challenges in Differentially-Private Federated Survival Analysis of Medical DataACM Conference on Health, Inference, and Learning (ACM CHIL), 2022 Shadi Rahimian Raouf Kerkouche I. Kurth Mario Fritz FedML 90 13 0 08 Feb 2022
Survey on Federated Learning Threats: concepts, taxonomy on attacks and defences, experimental study and challengesInformation Fusion (Inf. Fusion), 2022 Nuria Rodríguez-Barroso Daniel Jiménez López M. V. Luzón Francisco Herrera Eugenio Martínez-Cámara FedML 129 263 0 20 Jan 2022
Get your Foes Fooled: Proximal Gradient Split Learning for Defense against Model Inversion Attacks on IoMT dataIEEE Transactions on Network Science and Engineering (IEEE T-NSE), 2022 Sunder Ali Khowaja I. Lee Kapal Dev M. Jarwar N. Qureshi AAML 152 19 0 12 Jan 2022
An Interpretable Federated Learning-based Network Intrusion Detection Framework Tian Dong Song Li Han Qiu Jialiang Lu FedML 91 20 0 10 Jan 2022
APRIL: Finding the Achilles' Heel on Privacy for Vision TransformersComputer Vision and Pattern Recognition (CVPR), 2021 Jiahao Lu Xi Sheryl Zhang Tianli Zhao Xiangyu He Jian Cheng ViT PILM 104 28 0 28 Dec 2021
Gradient Leakage Attack Resilient Deep LearningIEEE Transactions on Information Forensics and Security (IEEE TIFS), 2021 Wenqi Wei Ling Liu SILM PILM AAML 118 57 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 163 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 166 22 0 10 Dec 2021
Location Leakage in Federated Signal MapsIEEE Transactions on Mobile Computing (IEEE TMC), 2021 Evita Bakopoulou Justin Ley Jiang Zhang Konstantinos Psounis A. Markopoulou FedML 154 5 0 07 Dec 2021
When the Curious Abandon Honesty: Federated Learning Is Not PrivateEuropean Symposium on Security and Privacy (EuroS&P), 2021 Franziska Boenisch Adam Dziedzic R. Schuster Ali Shahin Shamsabadi Ilia Shumailov Nicolas Papernot FedML AAML 196 214 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 143 324 0 30 Nov 2021
Understanding Training-Data Leakage from Gradients in Neural Networks for Image Classification Cangxiong Chen Neill D. F. Campbell FedML 93 27 0 19 Nov 2021
FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated LearningInternational Joint Conference on Artificial Intelligence (IJCAI), 2021 Yuezhou Wu Yan Kang Jiahuan Luo Yuanqin He Qiang Yang FedML AAML 199 82 0 16 Nov 2021
Bayesian Framework for Gradient Leakage Mislav Balunović Dimitar I. Dimitrov Robin Staab Martin Vechev FedML 128 48 0 08 Nov 2021
Federated Learning Attacks Revisited: A Critical Discussion of Gaps, Assumptions, and Evaluation SetupsItalian National Conference on Sensors (INS), 2021 A. Wainakh Ephraim Zimmer Sandeep Subedi Jens Keim Tim Grube Shankar Karuppayah Alejandro Sánchez Guinea Max Mühlhäuser 104 15 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 161 36 0 02 Nov 2021
Revealing and Protecting Labels in Distributed TrainingNeural Information Processing Systems (NeurIPS), 2021 Trung D. Q. Dang Om Thakkar Swaroop Indra Ramaswamy Rajiv Mathews Peter Chin Franccoise Beaufays 58 28 0 31 Oct 2021
Efficient passive membership inference attack in federated learning Oualid Zari Chuan Xu Giovanni Neglia FedML 124 37 0 31 Oct 2021
Dynamic Differential-Privacy Preserving SGD Jian Du Song Li Xiangyi Chen Siheng Chen Mingyi Hong 134 41 0 30 Oct 2021
Gradient Inversion with Generative Image PriorNeural Information Processing Systems (NeurIPS), 2021 Jinwoo Jeon Jaechang Kim Kangwook Lee Sewoong Oh Jungseul Ok 107 175 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 191 179 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 198 161 0 25 Oct 2021
Towards General Deep Leakage in Federated Learning Fauzan Farooqui Yongli Mou Feifei Li Qing Li Oya Beyan Stefan Decker Chunming Rong FedML 130 61 0 18 Oct 2021
Federated Deep Learning with Bayesian Privacy Hanlin Gu Lixin Fan Bowen Li Jie Li Yan Kang Xingtai Lv Qiang Yang FedML 211 23 0 27 Sep 2021
Dropout against Deep Leakage from Gradients Yanchong Zheng FedML 90 4 0 25 Aug 2021