Inverting Gradients -- How easy is it to break privacy in federated learning?

31 March 2020

Papers citing "Inverting Gradients -- How easy is it to break privacy in federated learning?"

50 / 229 papers shown

Title
Privacy-preserving quantum federated learning via gradient hiding Changhao Li Niraj Kumar Zhixin Song Shouvanik Chakrabarti Marco Pistoia FedML 33 20 0 07 Dec 2023
A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective Xianghua Xie Chen Hu Hanchi Ren Jingjing Deng FedML AAML 50 19 0 27 Nov 2023
RAIFLE: Reconstruction Attacks on Interaction-based Federated Learning with Adversarial Data Manipulation Dzung Pham Shreyas Kulkarni Amir Houmansadr 33 0 0 29 Oct 2023
FLTrojan: Privacy Leakage Attacks against Federated Language Models Through Selective Weight Tampering Md. Rafi Ur Rashid Vishnu Asutosh Dasu Kang Gu Najrin Sultana Shagufta Mehnaz AAML FedML 46 10 0 24 Oct 2023
Text Embeddings Reveal (Almost) As Much As Text John X. Morris Volodymyr Kuleshov Vitaly Shmatikov Alexander M. Rush RALM 28 96 0 10 Oct 2023
FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation Xiang Liu Liangxi Liu Feiyang Ye Yunheng Shen Xia Li Linshan Jiang Jialin Li 36 4 0 30 Sep 2023
Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception? Xiaoxiao Sun Nidham Gazagnadou Vivek Sharma Lingjuan Lyu Hongdong Li Liang Zheng 47 8 0 22 Sep 2023
Communication Efficient Private Federated Learning Using Dithering Burak Hasircioglu Deniz Gunduz FedML 45 7 0 14 Sep 2023
Tackling the Non-IID Issue in Heterogeneous Federated Learning by Gradient Harmonization Xinyu Zhang Weiyu Sun Ying-Cong Chen FedML 36 5 0 13 Sep 2023
A Survey for Federated Learning Evaluations: Goals and Measures Di Chai Leye Wang Liu Yang Junxue Zhang Kai Chen Qian Yang ELM FedML 27 21 0 23 Aug 2023
GPFL: Simultaneously Learning Global and Personalized Feature Information for Personalized Federated Learning Jianqing Zhang Yang Hua Hao Wang Tao Song Zhengui Xue Ruhui Ma Jianyin Cao Haibing Guan 39 23 0 20 Aug 2023
Approximate and Weighted Data Reconstruction Attack in Federated Learning Yongcun Song Ziqi Wang Enrique Zuazua AAML FedML 29 4 0 13 Aug 2023
Feature Matching Data Synthesis for Non-IID Federated Learning Zijian Li Yuchang Sun Jiawei Shao Yuyi Mao Jessie Hui Wang Jun Zhang 28 20 0 09 Aug 2023
FLIPS: Federated Learning using Intelligent Participant Selection R. Bhope K.R. Jayaram N. Venkatasubramanian Ashish Verma Gegi Thomas FedML 29 3 0 07 Aug 2023
Enhanced Security with Encrypted Vision Transformer in Federated Learning Rei Aso Sayaka Shiota Hitoshi Kiya FedML 34 2 0 01 Aug 2023
Asynchronous Federated Learning with Bidirectional Quantized Communications and Buffered Aggregation Tomàs Ortega Hamid Jafarkhani FedML 36 6 0 01 Aug 2023
Compressed Private Aggregation for Scalable and Robust Federated Learning over Massive Networks Natalie Lang Nir Shlezinger Rafael G. L. DÓliveira S. E. Rouayheb FedML 75 4 0 01 Aug 2023
Samplable Anonymous Aggregation for Private Federated Data Analysis Kunal Talwar Shan Wang Audra McMillan Vojta Jina Vitaly Feldman ... Congzheng Song Karl Tarbe Sebastian Vogt L. Winstrom Shundong Zhou FedML 38 13 0 27 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 43 23 0 20 Jul 2023
Information-Theoretically Private Federated Submodel Learning with Storage Constrained Databases Sajani Vithana S. Ulukus FedML 20 0 0 12 Jul 2023
Privacy-Preserving Graph Machine Learning from Data to Computation: A Survey Dongqi Fu Wenxuan Bao Ross Maciejewski Hanghang Tong Jingrui He 44 9 0 10 Jul 2023
Bounding data reconstruction attacks with the hypothesis testing interpretation of differential privacy Georgios Kaissis Jamie Hayes Alexander Ziller Daniel Rueckert AAML 45 11 0 08 Jul 2023
Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses G. Buzaglo Niv Haim Gilad Yehudai Gal Vardi Yakir Oz Yaniv Nikankin Michal Irani 34 10 0 04 Jul 2023
An Efficient Virtual Data Generation Method for Reducing Communication in Federated Learning Cheng Yang Xue Yang Dongxian Wu Xiaohu Tang FedML 29 0 0 21 Jun 2023
Theoretically Principled Federated Learning for Balancing Privacy and Utility Xiaojin Zhang Wenjie Li Kai Chen Shutao Xia Qian Yang FedML 25 9 0 24 May 2023
Gradient Leakage Defense with Key-Lock Module for Federated Learning Hanchi Ren Jingjing Deng Xianghua Xie Xiaoke Ma Jianfeng Ma FedML 37 2 0 06 May 2023
Incentivising the federation: gradient-based metrics for data selection and valuation in private decentralised training Dmitrii Usynin Daniel Rueckert Georgios Kaissis FedML 28 2 0 04 May 2023
A Game-theoretic Framework for Privacy-preserving Federated Learning Xiaojin Zhang Lixin Fan Si-Yi Wang Wenjie Li Kai Chen Qiang Yang FedML 31 4 0 11 Apr 2023
RecUP-FL: Reconciling Utility and Privacy in Federated Learning via User-configurable Privacy Defense Yue-li Cui Syed Imran Ali Meerza Zhuohang Li Luyang Liu Jiaxin Zhang Jian-Dong Liu AAML FedML 34 4 0 11 Apr 2023
Robust and IP-Protecting Vertical Federated Learning against Unexpected Quitting of Parties Jingwei Sun Zhixu Du Anna Dai Saleh Baghersalimi Alireza Amirshahi David Atienza Yiran Chen FedML 21 8 0 28 Mar 2023
The Resource Problem of Using Linear Layer Leakage Attack in Federated Learning Joshua C. Zhao A. Elkordy Atul Sharma Yahya H. Ezzeldin A. Avestimehr S. Bagchi FedML 45 12 0 27 Mar 2023
Federated Learning without Full Labels: A Survey Yilun Jin Yang Liu Kai Chen Qian Yang FedML 17 26 0 25 Mar 2023
A Survey on Class Imbalance in Federated Learning Jing Zhang Chuanwen Li Jianzgong Qi Jiayuan He FedML 47 13 0 21 Mar 2023
PFSL: Personalized & Fair Split Learning with Data & Label Privacy for thin clients Manas Wadhwa Gagan Raj Gupta Ashutosh Sahu Rahul Saini Vidhi Mittal FedML 24 6 0 19 Mar 2023
Considerations on the Theory of Training Models with Differential Privacy Marten van Dijk Phuong Ha Nguyen FedML 31 2 0 08 Mar 2023
Private Read-Update-Write with Controllable Information Leakage for Storage-Efficient Federated Learning with Top $r$ Sparsification Sajani Vithana S. Ulukus FedML 33 5 0 07 Mar 2023
Active Membership Inference Attack under Local Differential Privacy in Federated Learning Truc D. T. Nguyen Phung Lai K. Tran Nhathai Phan My T. Thai FedML 32 18 0 24 Feb 2023
Personalized Decentralized Federated Learning with Knowledge Distillation Eunjeong Jeong Marios Kountouris FedML 32 16 0 23 Feb 2023
Data-Free Diversity-Based Ensemble Selection For One-Shot Federated Learning in Machine Learning Model Market Naibo Wang Wen-Yu Feng Fusheng Liu Moming Duan See-Kiong Ng FedML 28 6 0 23 Feb 2023
Personalized Privacy-Preserving Framework for Cross-Silo Federated Learning Van Tuan Tran Huy Hieu Pham Kok-Seng Wong FedML 39 7 0 22 Feb 2023
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy Yifei Zhang Dun Zeng Jinglong Luo Zenglin Xu Irwin King FedML 84 48 0 21 Feb 2023
Speech Privacy Leakage from Shared Gradients in Distributed Learning Zhuohang Li Jiaxin Zhang Jian-Dong Liu FedML 32 1 0 21 Feb 2023
ByzSecAgg: A Byzantine-Resistant Secure Aggregation Scheme for Federated Learning Based on Coded Computing and Vector Commitment Tayyebeh Jahani-Nezhad M. Maddah-ali Giuseppe Caire FedML 35 2 0 20 Feb 2023
Personalized and privacy-preserving federated heterogeneous medical image analysis with PPPML-HMI Juexiao Zhou Longxi Zhou Di Wang Xiaopeng Xu Haoyang Li Yuetan Chu Wenkai Han Xin Gao 30 20 0 20 Feb 2023
Bounding Training Data Reconstruction in DP-SGD Jamie Hayes Saeed Mahloujifar Borja Balle AAML FedML 40 39 0 14 Feb 2023
Does Federated Learning Really Need Backpropagation? H. Feng Tianyu Pang Chao Du Wei Chen Shuicheng Yan Min Lin FedML 36 10 0 28 Jan 2023
Differentially Private Federated Clustering over Non-IID Data Yiwei Li Shuai Wang Chong-Yung Chi Tony Q.S. Quek FedML 33 13 0 03 Jan 2023
Unlocking Metaverse-as-a-Service The three pillars to watch: Privacy and Security, Edge Computing, and Blockchain Vesal Ahsani Alireza Rahimi Mehdi Letafati B. Khalaj 36 15 0 01 Jan 2023
Model Segmentation for Storage Efficient Private Federated Learning with Top $r$ Sparsification Sajani Vithana S. Ulukus FedML 26 5 0 22 Dec 2022
Differentially Private Decentralized Optimization with Relay Communication Luqing Wang Luyao Guo Shaofu Yang Xinli Shi 30 0 0 21 Dec 2022