iDLG: Improved Deep Leakage from Gradients

8 January 2020

Papers citing "iDLG: Improved Deep Leakage from Gradients"

50 / 349 papers shown

Title
Prospects of Privacy Advantage in Quantum Machine Learning Jamie Heredge Niraj Kumar Dylan Herman Shouvanik Chakrabarti Romina Yalovetzky Shree Hari Sureshbabu Changhao Li Marco Pistoia 155 7 0 14 May 2024
A Survey on Privacy-Preserving Caching at Network Edge: Classification, Solutions, and ChallengesACM Computing Surveys (ACM CSUR), 2024 Xianzhi Zhang Yipeng Zhou Di Wu Shazia Riaz Quan Z. Sheng Di Wu Linchang Xiao 71 7 0 03 May 2024
Recovering Labels from Local Updates in Federated Learning Huancheng Chen H. Vikalo FedML AAML 71 7 0 02 May 2024
Advances and Open Challenges in Federated Learning with Foundation Models Chao Ren Han Yu Hongyi Peng Xiaoli Tang Anran Li ... A. Tan Bo Zhao Xiaoxiao Li Zengxiang Li Qiang Yang FedML AIFin AI4CE 242 27 0 23 Apr 2024
Beyond Noise: Privacy-Preserving Decentralized Learning with Virtual Nodes Sayan Biswas Mathieu Even Anne-Marie Kermarrec Laurent Massoulie Rafael Pires Rishi Sharma M. Vos 127 5 0 15 Apr 2024
On the Efficiency of Privacy Attacks in Federated Learning Nawrin Tabassum Ka-Ho Chow Xuyu Wang Wenbin Zhang Yanzhao Wu FedML 107 5 0 15 Apr 2024
You Can Use But Cannot Recognize: Preserving Visual Privacy in Deep Neural Networks Qiushi Li Yan Zhang Ju Ren Qi Li Yaoxue Zhang AAML PICV 132 27 0 05 Apr 2024
Learn What You Want to Unlearn: Unlearning Inversion Attacks against Machine UnlearningIEEE Symposium on Security and Privacy (S&P), 2024 Hongsheng Hu Shuo Wang Tian Dong Minhui Xue AAML 141 40 0 04 Apr 2024
Leak and Learn: An Attacker's Cookbook to Train Using Leaked Data from Federated Learning Joshua C. Zhao Ahaan Dabholkar Atul Sharma Saurabh Bagchi FedML 117 3 0 26 Mar 2024
Enabling Privacy-preserving Model Evaluation in Federated Learning via Fully Homomorphic Encryption Cem Ata Baykara Ali Burak Ünal Mete Akgün FedML 67 0 0 21 Mar 2024
Efficient and Privacy-Preserving Federated Learning based on Full Homomorphic Encryption Yuqi Guo Lin Li Zhongxiang Zheng Hanrui Yun Ruoyan Zhang Xiaolin Chang Zhixuan Gao FedML 90 5 0 18 Mar 2024
Pencil: Private and Extensible Collaborative Learning without the Non-Colluding Assumption Xuanqi Liu Zhuotao Liu Qi Li Ke Xu Mingwei Xu 98 11 0 17 Mar 2024
Adaptive Hybrid Masking Strategy for Privacy-Preserving Face Recognition Against Model Inversion Attack Yinggui Wang Yuanqing Huang Jianshu Li Le Yang Kai Song Lei Wang AAML PICV 170 1 0 14 Mar 2024
RAF-GI: Towards Robust, Accurate and Fast-Convergent Gradient Inversion Attack in Federated Learning Can Liu Jin Wang Dong-Yang Yu AAML 59 1 0 13 Mar 2024
MGIC: A Multi-Label Gradient Inversion Attack based on Canny Edge Detection on Federated Learning Can Liu Jin Wang 154 1 0 13 Mar 2024
Fluent: Round-efficient Secure Aggregation for Private Federated Learning Xincheng Li Jianting Ning G. Poh Leo Yu Zhang Xinchun Yin Tianwei Zhang FedML 98 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 138 12 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 174 14 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 88 7 0 29 Feb 2024
How to Privately Tune Hyperparameters in Federated Learning? Insights from a Benchmark Study Natalija Mitic Apostolos Pyrgelis Sinem Sav FedML 207 2 0 25 Feb 2024
Privacy Attacks in Decentralized Learning Abdellah El Mrini Edwige Cyffers A. Bellet 208 8 0 15 Feb 2024
Towards Eliminating Hard Label Constraints in Gradient Inversion AttacksInternational Conference on Learning Representations (ICLR), 2024 Yanbo Wang Jian Liang Ran He AAML 107 7 0 05 Feb 2024
Survey of Privacy Threats and Countermeasures in Federated Learning M. Hayashitani Junki Mori Isamu Teranishi FedML 220 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 121 7 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 186 6 0 22 Jan 2024
AIJack: Let's Hijack AI! Security and Privacy Risk Simulator for Machine Learning Hideaki Takahashi SILM 154 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 109 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 149 69 0 27 Dec 2023
FedDMF: Privacy-Preserving User Attribute Prediction using Deep Matrix Factorization Ming Cheung 64 0 0 24 Dec 2023
Foreseeing Reconstruction Quality of Gradient Inversion: An Optimization Perspective H. Hong Yooshin Cho Hanbyel Cho Jaesung Ahn Junmo Kim 87 1 0 19 Dec 2023
PPIDSG: A Privacy-Preserving Image Distribution Sharing Scheme with GAN in Federated LearningAAAI Conference on Artificial Intelligence (AAAI), 2023 Yuting Ma Yuanzhi Yao Xiaohua Xu FedML 89 7 0 16 Dec 2023
Privacy-Aware Document Visual Question AnsweringIEEE International Conference on Document Analysis and Recognition (ICDAR), 2023 Rubèn Pérez Tito Khanh Nguyen Marlon Tobaben Raouf Kerkouche Mohamed Ali Souibgui ... Lei Kang Ernest Valveny Antti Honkela Mario Fritz Dimosthenis Karatzas 138 15 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 137 5 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 142 4 0 10 Dec 2023
Privacy-preserving quantum federated learning via gradient hiding Changhao Li Niraj Kumar Zhixin Song Shouvanik Chakrabarti Marco Pistoia FedML 169 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 122 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 173 30 0 27 Nov 2023
OASIS: Offsetting Active Reconstruction Attacks in Federated LearningIEEE International Conference on Distributed Computing Systems (ICDCS), 2023 Tre' R. Jeter Truc D. T. Nguyen Raed Alharbi My T. Thai AAML 127 0 0 23 Nov 2023
Scale-MIA: A Scalable Model Inversion Attack against Secure Federated Learning via Latent Space ReconstructionNetwork and Distributed System Security Symposium (NDSS), 2023 Shanghao Shi Ning Wang Yang Xiao Chaoyu Zhang Yi Shi Y. T. Hou W. Lou 118 13 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 120 2 0 08 Nov 2023
PriPrune: Quantifying and Preserving Privacy in Pruned Federated LearningACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS), 2023 Tianyue Chu Mengwei Yang Nikolaos Laoutaris A. Markopoulou 142 8 0 30 Oct 2023
Maximum Knowledge Orthogonality Reconstruction with Gradients in Federated LearningIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2023 Feng Wang Senem Velipasalar M. C. Gursoy 101 2 0 30 Oct 2023
Robust and Actively Secure Serverless Collaborative LearningNeural Information Processing Systems (NeurIPS), 2023 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 103 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 284 13 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 232 58 0 16 Oct 2023
Text Embeddings Reveal (Almost) As Much As TextConference on Empirical Methods in Natural Language Processing (EMNLP), 2023 John X. Morris Volodymyr Kuleshov Vitaly Shmatikov Alexander M. Rush RALM 173 151 0 10 Oct 2023
Source Inference Attacks: Beyond Membership Inference Attacks in Federated LearningIEEE Transactions on Dependable and Secure Computing (IEEE TDSC), 2023 Hongsheng Hu Xuyun Zhang Z. Salcic Lichao Sun K. Choo Gillian Dobbie 114 24 0 30 Sep 2023
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 180 11 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 244 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 254 9 0 22 Sep 2023