iDLG: Improved Deep Leakage from Gradients

8 January 2020

Papers citing "iDLG: Improved Deep Leakage from Gradients"

50 / 352 papers shown

Title
Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception?Neural Information Processing Systems (NeurIPS), 2023 Xiaoxiao Sun Nidham Gazagnadou Vivek Sharma Lingjuan Lyu Hongdong Li Liang Zheng 196 12 0 22 Sep 2023
Understanding Deep Gradient Leakage via Inversion Influence FunctionsNeural Information Processing Systems (NeurIPS), 2023 Haobo Zhang Junyuan Hong Yuyang Deng M. Mahdavi Jiayu Zhou FedML 282 9 0 22 Sep 2023
Expressive variational quantum circuits provide inherent privacy in federated learning Niraj Kumar Jamie Heredge Changhao Li Shaltiel Eloul Shree Hari Sureshbabu Marco Pistoia FedML 270 11 0 22 Sep 2023
Client-side Gradient Inversion Against Federated Learning from Poisoning Jiaheng Wei Yanjun Zhang Leo Yu Zhang Chao Chen Shirui Pan Kok-Leong Ong Jinchao Zhang Yang Xiang AAML 120 5 0 14 Sep 2023
SABLE: Secure And Byzantine robust LEarning Antoine Choffrut R. Guerraoui Rafael Pinot Renaud Sirdey John Stephan Martin Zuber AAML 284 2 0 11 Sep 2023
Privacy Preserving Federated Learning with Convolutional Variational Bottlenecks Daniel Scheliga Patrick Mäder M. Seeland FedML AAML 191 7 0 08 Sep 2023
Adversarial Predictions of Data Distributions Across Federated Internet-of-Things DevicesWorld Forum on Internet of Things (WF-IoT), 2023 Samir Rajani Dario Dematties Nathaniel Hudson Kyle Chard N. Ferrier R. Sankaran P. Beckman FedML 94 0 0 28 Aug 2023
ULDP-FL: Federated Learning with Across Silo User-Level Differential PrivacyProceedings of the VLDB Endowment (PVLDB), 2023 Fumiyuki Kato Li Xiong Shun Takagi Yang Cao Masatoshi Yoshikawa FedML 172 7 0 23 Aug 2023
Approximate and Weighted Data Reconstruction Attack in Federated Learning Yongcun Song Ziqi Wang Enrique Zuazua AAML FedML 138 6 0 13 Aug 2023
FLShield: A Validation Based Federated Learning Framework to Defend Against Poisoning AttacksIEEE Symposium on Security and Privacy (IEEE S&P), 2023 Ehsanul Kabir Zeyu Song Md Rafi Ur Rashid Shagufta Mehnaz 114 18 0 10 Aug 2023
Feature Matching Data Synthesis for Non-IID Federated LearningIEEE Transactions on Mobile Computing (IEEE TMC), 2023 Zijian Li Yuchang Sun Jiawei Shao Yuyi Mao Jessie Hui Wang Jun Zhang 101 29 0 09 Aug 2023
GIFD: A Generative Gradient Inversion Method with Feature Domain OptimizationIEEE International Conference on Computer Vision (ICCV), 2023 Hao Fang Bin Chen Xuan Wang Zhi Wang Shutao Xia 219 49 0 09 Aug 2023
FLIPS: Federated Learning using Intelligent Participant SelectionInternational Middleware Conference (Middleware), 2023 R. Bhope K.R. Jayaram N. Venkatasubramanian Ashish Verma Gegi Thomas FedML 198 5 0 07 Aug 2023
Label Inference Attacks against Node-level Vertical Federated GNNs Marco Arazzi Mauro Conti Stefanos Koffas Marina Krček Antonino Nocera S. Picek Jing Xu FedML AAML 177 1 0 04 Aug 2023
Compressed Private Aggregation for Scalable and Robust Federated Learning over Massive NetworksIEEE Transactions on Mobile Computing (IEEE TMC), 2023 Natalie Lang Stefano Rini Rafael G. L. DÓliveira S. E. Rouayheb FedML 297 7 0 01 Aug 2023
On the Trustworthiness Landscape of State-of-the-art Generative Models: A Survey and OutlookInternational Journal of Computer Vision (IJCV), 2023 Mingyuan Fan Chengyu Wang Cen Chen Yang Liu Jun Huang HILM 159 9 0 31 Jul 2023
Samplable Anonymous Aggregation for Private Federated Data AnalysisConference on Computer and Communications Security (CCS), 2023 Kunal Talwar Shan Wang Audra McMillan Vojta Jina Vitaly Feldman ... Congzheng Song Karl Tarbe Sebastian Vogt L. Winstrom Shundong Zhou FedML 275 17 0 27 Jul 2023
Mitigating Cross-client GANs-based Attack in Federated Learning Hong Huang Xinyu Lei Tao Xiang AAML 253 2 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 222 36 0 20 Jul 2023
Secure and Fast Asynchronous Vertical Federated Learning via Cascaded Hybrid OptimizationMachine-mediated learning (ML), 2023 Ganyu Wang Qingsong Zhang Li Xiang Boyu Wang Bin Gu Charles Ling FedML 157 6 0 28 Jun 2023
Federated Generative Learning with Foundation Models Jie Zhang Xiaohua Qi Bo Zhao FedML 180 26 0 28 Jun 2023
Practical Privacy-Preserving Gaussian Process Regression via Secret SharingConference on Uncertainty in Artificial Intelligence (UAI), 2023 Jinglong Luo Yehong Zhang Jiaqi Zhang Shuang Qin Haibo Wang Yue Yu Zenglin Xu 125 7 0 26 Jun 2023
Privacy and Fairness in Federated Learning: on the Perspective of Trade-offACM Computing Surveys (ACM Comput. Surv.), 2023 Huiqiang Chen Tianqing Zhu Tao Zhang Wanlei Zhou Philip S. Yu FedML 176 66 0 25 Jun 2023
Your Room is not Private: Gradient Inversion Attack on Reinforcement LearningIEEE International Conference on Robotics and Automation (ICRA), 2023 Miao Li Wenhao Ding Ding Zhao AAML 134 3 0 15 Jun 2023
Temporal Gradient Inversion Attacks with Robust OptimizationIEEE Transactions on Dependable and Secure Computing (IEEE TDSC), 2023 Bowen Li Jie Li Hanlin Gu Ruoxin Chen Jie Li Chentao Wu Na Ruan Xueming Si Lixin Fan AAML 124 3 0 13 Jun 2023
SRATTA : Sample Re-ATTribution Attack of Secure Aggregation in Federated LearningInternational Conference on Machine Learning (ICML), 2023 Tanguy Marchand Regis Loeb Ulysse Marteau-Ferey Jean Ogier du Terrail Arthur Pignet FedML 139 5 0 13 Jun 2023
FheFL: Fully Homomorphic Encryption Friendly Privacy-Preserving Federated Learning with Byzantine Users Y. Rahulamathavan Charuka Herath Xiaolan Liu S. Lambotharan Carsten Maple 202 19 0 08 Jun 2023
FedVal: Different good or different bad in federated learning Viktor Valadi Xinchi Qiu Pedro Gusmão Nicholas D. Lane Mina Alibeigi FedML AAML 155 7 0 06 Jun 2023
Avoid Adversarial Adaption in Federated Learning by Multi-Metric Investigations T. Krauß Alexandra Dmitrienko AAML 176 6 0 06 Jun 2023
Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning Kostadin Garov Dimitar I. Dimitrov Nikola Jovanović Martin Vechev AAML FedML 268 11 0 05 Jun 2023
FedCIP: Federated Client Intellectual Property Protection with Traitor Tracking Junchuan Liang Rong Wang FedML 146 19 0 02 Jun 2023
Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated LearningInternational Conference on Machine Learning (ICML), 2023 Junyi Zhu Ruicong Yao Matthew B. Blaschko FedML 205 12 0 31 May 2023
A Meta-learning Framework for Tuning Parameters of Protection Mechanisms in Trustworthy Federated LearningACM Transactions on Intelligent Systems and Technology (ACM TIST), 2023 Xiaojin Zhang Weijing Chen Lixin Fan Kai Chen Qiang Yang FedML 207 9 0 28 May 2023
Secure Vertical Federated Learning Under Unreliable Connectivity Xinchi Qiu Heng Pan Wanru Zhao Yan Gao Pedro Gusmão William F. Shen Chenyang Ma Nicholas D. Lane FedML 162 3 0 26 May 2023
Theoretically Principled Federated Learning for Balancing Privacy and Utility Xiaojin Zhang Wenjie Li Kai Chen Shutao Xia Qian Yang FedML 143 10 0 24 May 2023
Evaluating Privacy Leakage in Split Learning Xinchi Qiu Ilias Leontiadis Luca Melis Alex Sablayrolles Pierre Stock 184 6 0 22 May 2023
Efficient Vertical Federated Learning with Secure Aggregation Xinchi Qiu Heng Pan Wanru Zhao Chenyang Ma Pedro Porto Buarque de Gusmão Nicholas D. Lane FedML 121 4 0 18 May 2023
PrivaScissors: Enhance the Privacy of Collaborative Inference through the Lens of Mutual Information Lin Duan Jingwei Sun Yiran Chen M. Gorlatova 81 5 0 17 May 2023
Securing Distributed SGD against Gradient Leakage ThreatsIEEE Transactions on Parallel and Distributed Systems (TPDS), 2023 Wenqi Wei Ling Liu Jingya Zhou Ka-Ho Chow Yanzhao Wu FedML 112 26 0 10 May 2023
Towards Achieving Near-optimal Utility for Privacy-Preserving Federated Learning via Data Generation and Parameter Distortion Xiaojin Zhang Kai Chen Qian Yang FedML 132 6 0 07 May 2023
Gradient Leakage Defense with Key-Lock Module for Federated Learning Hanchi Ren Jingjing Deng Xianghua Xie FedML 288 2 0 06 May 2023
Sentence Embedding Leaks More Information than You Expect: Generative Embedding Inversion Attack to Recover the Whole SentenceAnnual Meeting of the Association for Computational Linguistics (ACL), 2023 Haoran Li Mingshi Xu Yangqiu Song 197 69 0 04 May 2023
FedCBO: Reaching Group Consensus in Clustered Federated Learning through Consensus-based OptimizationJournal of machine learning research (JMLR), 2023 J. Carrillo Nicolas García Trillos Sixu Li Yuhua Zhu FedML 100 23 0 04 May 2023
Optimizing Privacy, Utility and Efficiency in Constrained Multi-Objective Federated Learning Weijing Chen Hanlin Gu Xingxing Tang Yuanqin He Yuzhu Zhang Jinnan He Yuxing Han Lixin Fan Kai Chen Qiang Yang FedML 250 19 0 29 Apr 2023
Breaching FedMD: Image Recovery via Paired-Logits Inversion AttackComputer Vision and Pattern Recognition (CVPR), 2023 Hideaki Takahashi Jingjing Liu Yang Liu FedML 142 13 0 22 Apr 2023
A Game-theoretic Framework for Privacy-preserving Federated LearningACM Transactions on Intelligent Systems and Technology (ACM TIST), 2023 Xiaojin Zhang Lixin Fan Si-Yi Wang Wenjie Li Kai Chen Qiang Yang FedML 191 5 0 11 Apr 2023
RecUP-FL: Reconciling Utility and Privacy in Federated Learning via User-configurable Privacy DefenseACM Asia Conference on Computer and Communications Security (AsiaCCS), 2023 Yue-li Cui Syed Imran Ali Meerza Zhuohang Li Luyang Liu Jiaxin Zhang Jian-Dong Liu AAML FedML 155 5 0 11 Apr 2023
Secure Federated Learning against Model Poisoning Attacks via Client Filtering D. Yaldiz Tuo Zhang Salman Avestimehr AAML FedML 188 16 0 31 Mar 2023
Robust and IP-Protecting Vertical Federated Learning against Unexpected Quitting of PartiesBigData Congress [Services Society] (BSS), 2023 Jingwei Sun Zhixu Du Anna Dai Saleh Baghersalimi Alireza Amirshahi David Atienza Yiran Chen FedML 120 8 0 28 Mar 2023
The Resource Problem of Using Linear Layer Leakage Attack in Federated LearningComputer Vision and Pattern Recognition (CVPR), 2023 Joshua C. Zhao A. Elkordy Atul Sharma Yahya H. Ezzeldin A. Avestimehr S. Bagchi FedML 102 14 0 27 Mar 2023