iDLG: Improved Deep Leakage from Gradients

8 January 2020

Papers citing "iDLG: Improved Deep Leakage from Gradients"

50 / 334 papers shown

Title
Fluent: Round-efficient Secure Aggregation for Private Federated Learning Xincheng Li Jianting Ning G. Poh Leo Yu Zhang Xinchun Yin Tianwei Zhang FedML 86 2 0 10 Mar 2024
SPEAR:Exact Gradient Inversion of Batches in Federated Learning Dimitar I. Dimitrov Maximilian Baader Mark Niklas Muller Martin Vechev FedML 103 8 0 06 Mar 2024
Inf2Guard: An Information-Theoretic Framework for Learning Privacy-Preserving Representations against Inference Attacks Sayedeh Leila Noorbakhsh Binghui Zhang Yuan Hong Binghui Wang AAML 125 11 0 04 Mar 2024
PrivatEyes: Appearance-based Gaze Estimation Using Federated Secure Multi-Party Computation Mayar Elfares Pascal Reisert Zhiming Hu Wenwu Tang Ralf Küsters Andreas Bulling FedML 76 6 0 29 Feb 2024
How to Privately Tune Hyperparameters in Federated Learning? Insights from a Benchmark Study Natalija Mitic Apostolos Pyrgelis Sinem Sav FedML 142 1 0 25 Feb 2024
Privacy Attacks in Decentralized Learning Abdellah El Mrini Edwige Cyffers A. Bellet 112 7 0 15 Feb 2024
Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks Yanbo Wang Jian Liang Ran He AAML 103 6 0 05 Feb 2024
Survey of Privacy Threats and Countermeasures in Federated Learning M. Hayashitani Junki Mori Isamu Teranishi FedML 176 1 0 01 Feb 2024
Revisiting Gradient Pruning: A Dual Realization for Defending against Gradient Attacks Lulu Xue Shengshan Hu Rui-Qing Zhao Leo Yu Zhang Shengqing Hu Lichao Sun Dezhong Yao AAML 93 4 0 30 Jan 2024
Unraveling Attacks in Machine Learning-based IoT Ecosystems: A Survey and the Open Libraries Behind Them Chao-Jung Liu Boxi Chen Wei Shao Chris Zhang Kelvin Wong Yi Zhang 146 3 0 22 Jan 2024
AIJack: Let's Hijack AI! Security and Privacy Risk Simulator for Machine Learning Hideaki Takahashi SILM 114 2 0 29 Dec 2023
A Theoretical Analysis of Efficiency Constrained Utility-Privacy Bi-Objective Optimization in Federated Learning Hanlin Gu Xinyuan Zhao Gongxi Zhu Yuxing Han Yan Kang Lixin Fan Qiang Yang FedML 93 1 0 27 Dec 2023
Federated Continual Learning via Knowledge Fusion: A Survey Xin Yang Hao Yu Xin Gao Hao Wang Junbo Zhang Tianrui Li FedML 105 55 0 27 Dec 2023
FedDMF: Privacy-Preserving User Attribute Prediction using Deep Matrix Factorization Ming Cheung 52 0 0 24 Dec 2023
Foreseeing Reconstruction Quality of Gradient Inversion: An Optimization Perspective H. Hong Yooshin Cho Hanbyel Cho Jaesung Ahn Junmo Kim 63 1 0 19 Dec 2023
PPIDSG: A Privacy-Preserving Image Distribution Sharing Scheme with GAN in Federated Learning Yuting Ma Yuanzhi Yao Xiaohua Xu FedML 77 6 0 16 Dec 2023
Privacy-Aware Document Visual Question Answering Rubèn Pérez Tito Khanh Nguyen Marlon Tobaben Raouf Kerkouche Mohamed Ali Souibgui ... Lei Kang Ernest Valveny Antti Honkela Mario Fritz Dimosthenis Karatzas 94 14 0 15 Dec 2023
Enabling End-to-End Secure Federated Learning in Biomedical Research on Heterogeneous Computing Environments with APPFLx Trung-Hieu Hoang Jordan D. Fuhrman Ravi K. Madduri Miao Li Pranshu Chaturvedi ... Kibaek Kim Minseok Ryu Ryan Chard Eliu A. Huerta Maryellen L. Giger 113 6 0 14 Dec 2023
Beyond Gradient and Priors in Privacy Attacks: Leveraging Pooler Layer Inputs of Language Models in Federated Learning Jianwei Li Sheng Liu Qi Lei PILM SILM AAML 126 4 0 10 Dec 2023
Privacy-preserving quantum federated learning via gradient hiding Changhao Li Niraj Kumar Zhixin Song Shouvanik Chakrabarti Marco Pistoia FedML 113 30 0 07 Dec 2023
Exploring the Robustness of Decentralized Training for Large Language Models Lin Lu Chenxi Dai Wangcheng Tao Binhang Yuan Yanan Sun Pan Zhou 110 1 0 01 Dec 2023
A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective Xianghua Xie Chen Hu Hanchi Ren Jingjing Deng FedML AAML 137 30 0 27 Nov 2023
OASIS: Offsetting Active Reconstruction Attacks in Federated Learning Tre' R. Jeter Truc D. T. Nguyen Raed Alharbi My T. Thai AAML 103 0 0 23 Nov 2023
Scale-MIA: A Scalable Model Inversion Attack against Secure Federated Learning via Latent Space Reconstruction Shanghao Shi Ning Wang Yang Xiao Chaoyu Zhang Yi Shi Y. T. Hou W. Lou 106 11 0 10 Nov 2023
Edge-assisted U-Shaped Split Federated Learning with Privacy-preserving for Internet of Things Hengliang Tang Zihang Zhao Detian Liu Yang Cao Shiqiang Zhang Siqing You 96 2 0 08 Nov 2023
PriPrune: Quantifying and Preserving Privacy in Pruned Federated Learning Tianyue Chu Mengwei Yang Nikolaos Laoutaris A. Markopoulou 95 8 0 30 Oct 2023
Maximum Knowledge Orthogonality Reconstruction with Gradients in Federated Learning Feng Wang Senem Velipasalar M. C. Gursoy 77 2 0 30 Oct 2023
Robust and Actively Secure Serverless Collaborative Learning Olive Franzese Adam Dziedzic Christopher A. Choquette-Choo Mark R. Thomas Muhammad Ahmad Kaleem Stephan Rabanser Cong Fang Somesh Jha Nicolas Papernot Xiao Wang OOD 83 4 0 25 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 230 12 0 24 Oct 2023
Privacy in Large Language Models: Attacks, Defenses and Future Directions Haoran Li Yulin Chen Jinglong Luo Yan Kang Xiaojin Zhang Qi Hu Chunkit Chan Yangqiu Song PILM 157 51 0 16 Oct 2023
Text Embeddings Reveal (Almost) As Much As Text John X. Morris Volodymyr Kuleshov Vitaly Shmatikov Alexander M. Rush RALM 130 140 0 10 Oct 2023
Source Inference Attacks: Beyond Membership Inference Attacks in Federated Learning Hongsheng Hu Xuyun Zhang Z. Salcic Lichao Sun K. Choo Gillian Dobbie 82 19 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 136 9 0 22 Sep 2023
Understanding Deep Gradient Leakage via Inversion Influence Functions Haobo Zhang Junyuan Hong Yuyang Deng M. Mahdavi Jiayu Zhou FedML 151 8 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 171 9 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 96 3 0 14 Sep 2023
SABLE: Secure And Byzantine robust LEarning Antoine Choffrut R. Guerraoui Rafael Pinot Renaud Sirdey John Stephan Martin Zuber AAML 153 2 0 11 Sep 2023
Privacy Preserving Federated Learning with Convolutional Variational Bottlenecks Daniel Scheliga Patrick Mäder M. Seeland FedML AAML 107 5 0 08 Sep 2023
Adversarial Predictions of Data Distributions Across Federated Internet-of-Things Devices Samir Rajani Dario Dematties Nathaniel Hudson Kyle Chard N. Ferrier R. Sankaran P. Beckman FedML 50 0 0 28 Aug 2023
ULDP-FL: Federated Learning with Across Silo User-Level Differential Privacy Fumiyuki Kato Li Xiong Shun Takagi Yang Cao Masatoshi Yoshikawa FedML 132 6 0 23 Aug 2023
Approximate and Weighted Data Reconstruction Attack in Federated Learning Yongcun Song Ziqi Wang Enrique Zuazua AAML FedML 114 5 0 13 Aug 2023
FLShield: A Validation Based Federated Learning Framework to Defend Against Poisoning Attacks Ehsanul Kabir Zeyu Song Md Rafi Ur Rashid Shagufta Mehnaz 86 14 0 10 Aug 2023
Feature Matching Data Synthesis for Non-IID Federated Learning Zijian Li Yuchang Sun Jiawei Shao Yuyi Mao Jessie Hui Wang Jun Zhang 77 29 0 09 Aug 2023
GIFD: A Generative Gradient Inversion Method with Feature Domain Optimization Hao Fang Bin Chen Xuan Wang Zhi Wang Shutao Xia 157 40 0 09 Aug 2023
FLIPS: Federated Learning using Intelligent Participant Selection R. Bhope K.R. Jayaram N. Venkatasubramanian Ashish Verma Gegi Thomas FedML 126 3 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 109 1 0 04 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 225 6 0 01 Aug 2023
On the Trustworthiness Landscape of State-of-the-art Generative Models: A Survey and Outlook Mingyuan Fan Chengyu Wang Cen Chen Yang Liu Jun Huang HILM 123 5 0 31 Jul 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 187 15 0 27 Jul 2023
Mitigating Cross-client GANs-based Attack in Federated Learning Hong Huang Xinyu Lei Tao Xiang AAML 181 2 0 25 Jul 2023