iDLG: Improved Deep Leakage from Gradients

8 January 2020

Papers citing "iDLG: Improved Deep Leakage from Gradients"

50 / 349 papers shown

Title
Differentially Private Distributed Convex Optimization Minseok Ryu Kibaek Kim FedML 159 2 0 28 Feb 2023
Regulating Clients' Noise Adding in Federated Learning without Verification Shu Hong Lingjie Duan 67 0 0 24 Feb 2023
Personalized Privacy-Preserving Framework for Cross-Silo Federated LearningIEEE Transactions on Emerging Topics in Computing (IEEE TETC), 2023 Van Tuan Tran Huy Hieu Pham Kok-Seng Wong FedML 164 9 0 22 Feb 2023
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and PrivacyThe Web Conference (WWW), 2023 Yifei Zhang Dun Zeng Jinglong Luo Zenglin Xu Irwin King FedML 244 59 0 21 Feb 2023
Personalized and privacy-preserving federated heterogeneous medical image analysis with PPPML-HMImedRxiv (medRxiv), 2023 Juexiao Zhou Longxi Zhou Di Wang Xiaopeng Xu Haoyang Li Yuetan Chu Wenkai Han Xin Gao 131 23 0 20 Feb 2023
Bounding Training Data Reconstruction in DP-SGDNeural Information Processing Systems (NeurIPS), 2023 Jamie Hayes Saeed Mahloujifar Borja Balle AAML FedML 220 55 0 14 Feb 2023
On the Privacy-Robustness-Utility Trilemma in Distributed LearningInternational Conference on Machine Learning (ICML), 2023 Youssef Allouah R. Guerraoui Nirupam Gupta Rafael Pinot John Stephan FedML 118 31 0 09 Feb 2023
FedLAP-DP: Federated Learning by Sharing Differentially Private Loss ApproximationsProceedings on Privacy Enhancing Technologies (PoPETs), 2023 Hui-Po Wang Dingfan Chen Raouf Kerkouche Mario Fritz FedML DD 342 5 0 02 Feb 2023
Reconstructing Individual Data Points in Federated Learning Hardened with Differential Privacy and Secure AggregationEuropean Symposium on Security and Privacy (Euro S&P), 2023 Franziska Boenisch Adam Dziedzic R. Schuster Ali Shahin Shamsabadi Ilia Shumailov Nicolas Papernot FedML 176 28 0 09 Jan 2023
Recent Advances on Federated Learning: A Systematic SurveyNeurocomputing (Neurocomputing), 2023 Bingyan Liu Nuoyan Lv Yuanchun Guo Yawen Li FedML 184 133 0 03 Jan 2023
Mutual Information Regularization for Vertical Federated Learning Tianyuan Zou Yang Liu Ya-Qin Zhang AAML FedML 151 7 0 01 Jan 2023
Deep leakage from gradients Yaqiong Mu FedML 74 1 0 15 Dec 2022
Reconstructing Training Data from Model Gradient, ProvablyInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022 Zihan Wang Jason D. Lee Qi Lei FedML 183 33 0 07 Dec 2022
Refiner: Data Refining against Gradient Leakage Attacks in Federated Learning Mingyuan Fan Cen Chen Chengyu Wang Ximeng Liu Wenmeng Zhou AAML FedML 259 0 0 05 Dec 2022
Federated Learning Attacks and Defenses: A Survey Yao Chen Yijie Gui Hong Lin Wensheng Gan Yongdong Wu FedML 141 36 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 112 1 0 14 Nov 2022
Directional Privacy for Deep Learning Pedro Faustini Natasha Fernandes Shakila Mahjabin Tonni Annabelle McIver Mark Dras 124 3 0 09 Nov 2022
Privacy-Aware Compression for Federated Learning Through Numerical Mechanism DesignInternational Conference on Machine Learning (ICML), 2022 Chuan Guo Kamalika Chaudhuri Pierre Stock Michael G. Rabbat FedML 189 7 0 08 Nov 2022
Two Models are Better than One: Federated Learning Is Not Private For Google GBoard Next Word PredictionEuropean Symposium on Research in Computer Security (ESORICS), 2022 Mohamed Suliman D. Leith SILM FedML 101 8 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 164 3 0 28 Oct 2022
Mixed Precision Quantization to Tackle Gradient Leakage Attacks in Federated Learning Pretom Roy Ovi Emon Dey Nirmalya Roy A. Gangopadhyay FedML 98 6 0 22 Oct 2022
Analysing Training-Data Leakage from Gradients through Linear Systems and Gradient MatchingBritish Machine Vision Conference (BMVC), 2022 Cangxiong Chen Neill D. F. Campbell FedML 78 1 0 20 Oct 2022
How Does a Deep Learning Model Architecture Impact Its Privacy? A Comprehensive Study of Privacy Attacks on CNNs and TransformersUSENIX Security Symposium (USENIX Security), 2022 Guangsheng Zhang B. Liu Huan Tian Tianqing Zhu Ming Ding Wanlei Zhou PILM MIACV 153 8 0 20 Oct 2022
Learning to Invert: Simple Adaptive Attacks for Gradient Inversion in Federated LearningConference on Uncertainty in Artificial Intelligence (UAI), 2022 Ruihan Wu Xiangyu Chen Chuan Guo Kilian Q. Weinberger FedML 99 36 0 19 Oct 2022
Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and VulnerabilityInternational Conference on Machine Learning (ICML), 2022 Zhao Song Yitan Wang Zheng Yu Licheng Zhang FedML 148 31 0 15 Oct 2022
CrowdGuard: Federated Backdoor Detection in Federated LearningNetwork and Distributed System Security Symposium (NDSS), 2022 Phillip Rieger T. Krauß Markus Miettinen Alexandra Dmitrienko Ahmad-Reza Sadeghi Technical University Darmstadt AAML FedML 131 30 0 14 Oct 2022
FedDef: Defense Against Gradient Leakage in Federated Learning-based Network Intrusion Detection SystemsIEEE Transactions on Information Forensics and Security (IEEE TIFS), 2022 Jiahui Chen Yi Zhao Qi Li Xuewei Feng Ke Xu AAML FedML 187 22 0 08 Oct 2022
TabLeak: Tabular Data Leakage in Federated LearningInternational Conference on Machine Learning (ICML), 2022 Mark Vero Mislav Balunović Dimitar I. Dimitrov Martin Vechev FedML 113 11 0 04 Oct 2022
SecureFedYJ: a safe feature Gaussianization protocol for Federated LearningNeural Information Processing Systems (NeurIPS), 2022 Tanguy Marchand Boris Muzellec C. Béguier Jean Ogier du Terrail M. Andreux FedML 151 11 0 04 Oct 2022
A Secure Federated Learning Framework for Residential Short Term Load ForecastingIEEE Transactions on Smart Grid (IEEE Trans. Smart Grid), 2022 Muhammad Akbar Husnoo A. Anwar N. Hosseinzadeh S. Islam A. N. Mahmood R. Doss 178 43 0 29 Sep 2022
Concealing Sensitive Samples against Gradient Leakage in Federated LearningAAAI Conference on Artificial Intelligence (AAAI), 2022 Jing Wu Munawar Hayat Min Zhou Mehrtash Harandi FedML 96 14 0 13 Sep 2022
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning using Independent Component AnalysisInternational Conference on Machine Learning (ICML), 2022 Sanjay Kariyappa Chuan Guo Kiwan Maeng Wenjie Xiong G. E. Suh Moinuddin K. Qureshi Hsien-Hsin S. Lee FedML 110 39 0 12 Sep 2022
Secure Shapley Value for Cross-Silo Federated Learning (Technical Report)Proceedings of the VLDB Endowment (PVLDB), 2022 Shuyuan Zheng Yang Cao Masatoshi Yoshikawa FedML 159 33 0 11 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 134 15 0 08 Sep 2022
Trading Off Privacy, Utility and Efficiency in Federated LearningACM Transactions on Intelligent Systems and Technology (ACM TIST), 2022 Xiaojin Zhang Yan Kang Kai Chen Lixin Fan Qiang Yang FedML 269 63 0 01 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 143 0 0 29 Aug 2022
DPAUC: Differentially Private AUC Computation in Federated LearningAAAI Conference on Artificial Intelligence (AAAI), 2022 Jiankai Sun Xin Yang Yuanshun Yao Junyuan Xie Di Wu Chong-Jun Wang FedML 108 14 0 25 Aug 2022
Joint Privacy Enhancement and Quantization in Federated LearningIEEE Transactions on Signal Processing (IEEE Trans. Signal Process.), 2022 Natalie Lang Elad Sofer Tomer Shaked Stefano Rini FedML 143 60 0 23 Aug 2022
DHSA: Efficient Doubly Homomorphic Secure Aggregation for Cross-silo Federated LearningJournal of Supercomputing (JS), 2022 Zizhen Liu Si-Quan Chen Jing Ye Junfeng Fan Huawei Li Xiaowei Li FedML 100 20 0 15 Aug 2022
Dropout is NOT All You Need to Prevent Gradient LeakageAAAI Conference on Artificial Intelligence (AAAI), 2022 Daniel Scheliga Patrick Mäder M. Seeland FedML 147 17 0 12 Aug 2022
Privacy-Preserving Federated Recurrent Neural NetworksProceedings on Privacy Enhancing Technologies (PoPETs), 2022 Sinem Sav Abdulrahman Diaa Apostolos Pyrgelis Jean-Philippe Bossuat Jean-Pierre Hubaux FedML 137 8 0 28 Jul 2022
Is Vertical Logistic Regression Privacy-Preserving? A Comprehensive Privacy Analysis and Beyond Yuzheng Hu Tianle Cai Jinyong Shan Shange Tang Chaochao Cai Ethan Song Yue Liu Basel Alomair FedML AAML 100 10 0 19 Jul 2022
ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production ScaleKnowledge Discovery and Data Mining (KDD), 2022 Gopinath Chennupati Milind Rao Gurpreet Chadha Aaron Eakin A. Raju ... Andrew Oberlin Buddha Nandanoor Prahalad Venkataramanan Zheng Wu Pankaj Sitpure CLL 129 8 0 19 Jul 2022
Towards Privacy-Preserving Person Re-identification via Person Identify Shift Shuguang Dou Xinyang Jiang Qingsong Zhao Dongsheng Li Cairong Zhao 92 8 0 15 Jul 2022
Enhanced Security and Privacy via Fragmented Federated LearningIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022 N. Jebreel J. Domingo-Ferrer Alberto Blanco-Justicia David Sánchez FedML 134 33 0 13 Jul 2022
GOF-TTE: Generative Online Federated Learning Framework for Travel Time EstimationIEEE Internet of Things Journal (IEEE IoT J.), 2022 Zhiwen Zhang Hongjun Wang Jiyuan Chen Z. Fan Xuan Song Ryosuke Shibasaki FedML AI4TS 76 15 0 02 Jul 2022
Data Leakage in Federated Averaging Dimitar I. Dimitrov Mislav Balunović Nikola Konstantinov Martin Vechev FedML 123 38 0 24 Jun 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 108 4 0 21 Jun 2022
FedER: Federated Learning through Experience Replay and Privacy-Preserving Data SynthesisComputer Vision and Image Understanding (CVIU), 2022 M. Pennisi Federica Proietto Salanitri Giovanni Bellitto Bruno Casella Marco Aldinucci S. Palazzo C. Spampinato OOD 117 12 0 20 Jun 2022
A Survey on Gradient Inversion: Attacks, Defenses and Future DirectionsInternational Joint Conference on Artificial Intelligence (IJCAI), 2022 Rui Zhang Song Guo Junxiao Wang Xin Xie Dacheng Tao 112 46 0 15 Jun 2022