Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning

3 December 2018

Zhifei Zhang

Papers citing "Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning"

50 / 109 papers shown

Title
Dyn-D $^2$ P: Dynamic Differentially Private Decentralized Learning with Provable Utility Guarantee Zehan Zhu Yan Huang Xin Wang Shouling Ji Jinming Xu 26 0 0 10 May 2025
Towards Trustworthy Federated Learning with Untrusted Participants Youssef Allouah R. Guerraoui John Stephan FedML 55 0 0 03 May 2025
Theoretical Insights in Model Inversion Robustness and Conditional Entropy Maximization for Collaborative Inference Systems Song Xia Yi Yu Wenhan Yang Meiwen Ding Zhuo Chen Lingyu Duan Alex C. Kot Xudong Jiang 56 2 0 01 Mar 2025
A Survey of Model Extraction Attacks and Defenses in Distributed Computing Environments Kaixiang Zhao Lincan Li Kaize Ding Neil Zhenqiang Gong Yue Zhao Yushun Dong AAML 52 0 0 22 Feb 2025
Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning Saber Malekmohammadi Yaoliang Yu Yang Cao FedML 88 5 0 17 Feb 2025
Ten Challenging Problems in Federated Foundation Models Tao Fan Hanlin Gu Xuemei Cao Chee Seng Chan Qian Chen ... Y. Zhang Xiaojin Zhang Zhenzhe Zheng Lixin Fan Qiang Yang FedML 89 4 0 14 Feb 2025
Gradients Stand-in for Defending Deep Leakage in Federated Learning H. Yi H. Ren C. Hu Y. Li J. Deng Xin Xie FedML 32 0 0 11 Oct 2024
Balancing Security and Accuracy: A Novel Federated Learning Approach for Cyberattack Detection in Blockchain Networks Tran Viet Khoa Mohammad Abu Alsheikh Yibeltal Alem D. Hoang FedML 29 3 0 08 Sep 2024
Data Quality in Edge Machine Learning: A State-of-the-Art Survey M. D. Belgoumri Mohamed Reda Bouadjenek Sunil Aryal Hakim Hacid 41 1 0 01 Jun 2024
PrivSGP-VR: Differentially Private Variance-Reduced Stochastic Gradient Push with Tight Utility Bounds Zehan Zhu Yan Huang Xin Wang Jinming Xu 41 0 0 04 May 2024
State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey Chaoyu Zhang Shaoyu Li AILaw 50 3 0 25 Feb 2024
Cross-silo Federated Learning with Record-level Personalized Differential Privacy Junxu Liu Jian Lou Li Xiong Jinfei Liu Xiaofeng Meng 31 5 0 29 Jan 2024
Data-Agnostic Model Poisoning against Federated Learning: A Graph Autoencoder Approach Kai Li Jingjing Zheng Xinnan Yuan W. Ni Ozgur B. Akan H. Vincent Poor AAML 24 15 0 30 Nov 2023
A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective Xianghua Xie Chen Hu Hanchi Ren Jingjing Deng FedML AAML 44 19 0 27 Nov 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
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 7 0 22 Sep 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
Mitigating Cross-client GANs-based Attack in Federated Learning Hong Huang Xinyu Lei Tao Xiang AAML 55 1 0 25 Jul 2023
Blockchain-based Optimized Client Selection and Privacy Preserved Framework for Federated Learning Elizabeth Salesky Susanne Burger J. Niehues Huansheng Ning FedML 6 0 0 25 Jul 2023
Information-Theoretically Private Federated Submodel Learning with Storage Constrained Databases Sajani Vithana S. Ulukus FedML 20 0 0 12 Jul 2023
Avoid Adversarial Adaption in Federated Learning by Multi-Metric Investigations T. Krauß Alexandra Dmitrienko AAML 27 4 0 06 Jun 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
A Game-theoretic Framework for Privacy-preserving Federated Learning Xiaojin Zhang Lixin Fan Si-Yi Wang Wenjie Li Kai Chen Qiang Yang FedML 23 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 26 4 0 11 Apr 2023
Gradient Sparsification for Efficient Wireless Federated Learning with Differential Privacy Kang Wei Jun Li Chuan Ma Ming Ding Feng Shu Haitao Zhao Wen Chen Hongbo Zhu FedML 32 4 0 09 Apr 2023
Personalized Privacy-Preserving Framework for Cross-Silo Federated Learning Van Tuan Tran Huy Hieu Pham Kok-Seng Wong FedML 36 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 47 0 21 Feb 2023
Digital Privacy Under Attack: Challenges and Enablers Baobao Song Mengyue Deng Shiva Raj Pokhrel Qiujun Lan R. Doss Gang Li AAML 39 3 0 18 Feb 2023
Bounding Training Data Reconstruction in DP-SGD Jamie Hayes Saeed Mahloujifar Borja Balle AAML FedML 33 39 0 14 Feb 2023
GAN-based Vertical Federated Learning for Label Protection in Binary Classification Yujin Han Leying Guan FedML 35 0 0 04 Feb 2023
Modeling Global Distribution for Federated Learning with Label Distribution Skew Tao Sheng Cheng Shen Yuan Liu Yeyu Ou Zhe Qu Jianxin Wang FedML 27 7 0 17 Dec 2022
Straggler-Resilient Differentially-Private Decentralized Learning Yauhen Yakimenka Chung-Wei Weng Hsuan-Yin Lin E. Rosnes J. Kliewer 29 6 0 06 Dec 2022
Adap DP-FL: Differentially Private Federated Learning with Adaptive Noise Jie Fu Zhili Chen Xiao Han FedML 22 28 0 29 Nov 2022
DPD-fVAE: Synthetic Data Generation Using Federated Variational Autoencoders With Differentially-Private Decoder Bjarne Pfitzner B. Arnrich FedML 33 19 0 21 Nov 2022
SA-DPSGD: Differentially Private Stochastic Gradient Descent based on Simulated Annealing Jie Fu Zhili Chen Xinpeng Ling 25 0 0 14 Nov 2022
Local Model Reconstruction Attacks in Federated Learning and their Uses Ilias Driouich Chuan Xu Giovanni Neglia F. Giroire Eoin Thomas AAML FedML 32 2 0 28 Oct 2022
Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability Zhao-quan Song Yitan Wang Zheng Yu Licheng Zhang FedML 23 28 0 15 Oct 2022
In Differential Privacy, There is Truth: On Vote Leakage in Ensemble Private Learning Jiaqi Wang R. Schuster Ilia Shumailov David Lie Nicolas Papernot FedML 33 3 0 22 Sep 2022
Private Read Update Write (PRUW) in Federated Submodel Learning (FSL): Communication Efficient Schemes With and Without Sparsification Sajani Vithana S. Ulukus FedML 20 19 0 09 Sep 2022
Orchestrating Collaborative Cybersecurity: A Secure Framework for Distributed Privacy-Preserving Threat Intelligence Sharing J. Troncoso-Pastoriza Alain Mermoud Romain Bouyé Francesco Marino Jean-Philippe Bossuat Vincent Lenders Jean-Pierre Hubaux 32 3 0 06 Sep 2022
Fed-FSNet: Mitigating Non-I.I.D. Federated Learning via Fuzzy Synthesizing Network Jingcai Guo Song Guo Jie Zhang Ziming Liu FedML 25 15 0 21 Aug 2022
How Much Privacy Does Federated Learning with Secure Aggregation Guarantee? A. Elkordy Jiang Zhang Yahya H. Ezzeldin Konstantinos Psounis A. Avestimehr FedML 35 38 0 03 Aug 2022
Subject Membership Inference Attacks in Federated Learning Anshuman Suri Pallika H. Kanani Virendra J. Marathe Daniel W. Peterson 30 25 0 07 Jun 2022
Private Federated Submodel Learning with Sparsification Sajani Vithana S. Ulukus FedML 26 10 0 31 May 2022
Secure Federated Clustering Songze Li Sizai Hou Baturalp Buyukates A. Avestimehr FedML 23 9 0 31 May 2022
Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees Banghua Zhu Lun Wang Qi Pang Shuai Wang Jiantao Jiao D. Song Michael I. Jordan FedML 98 30 0 24 May 2022
LIA: Privacy-Preserving Data Quality Evaluation in Federated Learning Using a Lazy Influence Approximation Ljubomir Rokvic Panayiotis Danassis Sai Praneeth Karimireddy Boi Faltings TDI 27 1 0 23 May 2022
Symbolic analysis meets federated learning to enhance malware identifier Khanh-Huu-The Dam Charles-Henry Bertrand Van Ouytsel Axel Legay FedML 29 5 0 29 Apr 2022
AGIC: Approximate Gradient Inversion Attack on Federated Learning Jin Xu Chi Hong Jiyue Huang L. Chen Jérémie Decouchant AAML FedML 23 21 0 28 Apr 2022
A review of Federated Learning in Intrusion Detection Systems for IoT Aitor Belenguer J. Navaridas J. A. Pascual 25 15 0 26 Apr 2022