Protection Against Reconstruction and Its Applications in Private Federated Learning

3 December 2018

Papers citing "Protection Against Reconstruction and Its Applications in Private Federated Learning"

50 / 68 papers shown

Title
Cutting Through Privacy: A Hyperplane-Based Data Reconstruction Attack in Federated Learning Francesco Diana André Nusser Chuan Xu Giovanni Neglia 27 0 0 15 May 2025
Universally Harmonizing Differential Privacy Mechanisms for Federated Learning: Boosting Accuracy and Convergence Shuya Feng Meisam Mohammady Hanbin Hong Shenao Yan Ashish Kundu Binghui Wang Yuan Hong FedML 44 3 0 20 Jul 2024
Beyond Statistical Estimation: Differentially Private Individual Computation via Shuffling Shaowei Wang Changyu Dong Xiangfu Song Jin Li Zhili Zhou Di Wang Han Wu 41 0 0 26 Jun 2024
Universal Exact Compression of Differentially Private Mechanisms Yanxiao Liu Wei-Ning Chen Ayfer Özgür Cheuk Ting Li 42 2 0 28 May 2024
Federated learning with differential privacy and an untrusted aggregator Kunlong Liu Trinabh Gupta 50 0 0 17 Dec 2023
Federated Learning is Better with Non-Homomorphic Encryption Konstantin Burlachenko Abdulmajeed Alrowithi Fahad Ali Albalawi Peter Richtárik FedML 47 6 0 04 Dec 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
Exact Optimality of Communication-Privacy-Utility Tradeoffs in Distributed Mean Estimation Berivan Isik Wei-Ning Chen Ayfer Özgür Tsachy Weissman Albert No 61 19 0 08 Jun 2023
Privacy Amplification via Shuffling: Unified, Simplified, and Tightened Shaowei Wang FedML 26 9 0 11 Apr 2023
A Survey on Class Imbalance in Federated Learning Jing Zhang Chuanwen Li Jianzgong Qi Jiayuan He FedML 47 13 0 21 Mar 2023
Considerations on the Theory of Training Models with Differential Privacy Marten van Dijk Phuong Ha Nguyen FedML 28 2 0 08 Mar 2023
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy Natalia Ponomareva Hussein Hazimeh Alexey Kurakin Zheng Xu Carson E. Denison H. B. McMahan Sergei Vassilvitskii Steve Chien Abhradeep Thakurta 96 167 0 01 Mar 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
A Federated Approach for Hate Speech Detection Jay Gala Deep Gandhi Jash Mehta Zeerak Talat 21 4 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
FedGPO: Heterogeneity-Aware Global Parameter Optimization for Efficient Federated Learning Young Geun Kim Carole-Jean Wu FedML 22 5 0 30 Nov 2022
Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design Chuan Guo Kamalika Chaudhuri Pierre Stock Michael G. Rabbat FedML 33 7 0 08 Nov 2022
Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano Chuan Guo Alexandre Sablayrolles Maziar Sanjabi FedML 29 17 0 24 Oct 2022
Contraction of Locally Differentially Private Mechanisms S. Asoodeh Huanyu Zhang 26 10 0 24 Oct 2022
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings Jean Ogier du Terrail Samy Ayed Edwige Cyffers Felix Grimberg Chaoyang He ... Sai Praneeth Karimireddy Marco Lorenzi Giovanni Neglia Marc Tommasi M. Andreux FedML 47 142 0 10 Oct 2022
On the Stability Analysis of Open Federated Learning Systems Youbang Sun H. Fernando Tianyi Chen Shahin Shahrampour FedML 29 1 0 25 Sep 2022
Algorithms with More Granular Differential Privacy Guarantees Badih Ghazi Ravi Kumar Pasin Manurangsi Thomas Steinke 62 6 0 08 Sep 2022
Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks Chulin Xie Yunhui Long Pin-Yu Chen Qinbin Li Arash Nourian Sanmi Koyejo Bo Li FedML 43 13 0 08 Sep 2022
Privacy Aware Experimentation over Sensitive Groups: A General Chi Square Approach R. Friedberg Ryan M. Rogers 29 3 0 17 Aug 2022
Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM Chulin Xie Pin-Yu Chen Qinbin Li Arash Nourian Ce Zhang Bo Li FedML 38 16 0 20 Jul 2022
Enhanced Security and Privacy via Fragmented Federated Learning N. Jebreel J. Domingo-Ferrer Alberto Blanco-Justicia David Sánchez FedML 36 26 0 13 Jul 2022
sqSGD: Locally Private and Communication Efficient Federated Learning Yan Feng Tao Xiong Ruofan Wu Lingjuan Lv Leilei Shi FedML 28 2 0 21 Jun 2022
Nebula-I: A General Framework for Collaboratively Training Deep Learning Models on Low-Bandwidth Cloud Clusters Yang Xiang Zhihua Wu Weibao Gong Siyu Ding Xianjie Mo ... Yue Yu Ge Li Yu Sun Yanjun Ma Dianhai Yu 24 4 0 19 May 2022
Optimal Algorithms for Mean Estimation under Local Differential Privacy Hilal Asi Vitaly Feldman Kunal Talwar 40 41 0 05 May 2022
Reconstruction of univariate functions from directional persistence diagrams Aina Ferrà Carles Casacuberta O. Pujol 28 1 0 03 Mar 2022
One-bit Submission for Locally Private Quasi-MLE: Its Asymptotic Normality and Limitation Hajime Ono Kazuhiro Minami H. Hino 11 0 0 15 Feb 2022
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification Yuxin Wen Jonas Geiping Liam H. Fowl Micah Goldblum Tom Goldstein FedML 92 92 0 01 Feb 2022
Aggregation and Transformation of Vector-Valued Messages in the Shuffle Model of Differential Privacy Mary Scott Graham Cormode Carsten Maple 45 11 0 31 Jan 2022
Reconstructing Training Data with Informed Adversaries Borja Balle Giovanni Cherubin Jamie Hayes MIACV AAML 43 158 0 13 Jan 2022
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey Shangwei Guo Xu Zhang Feiyu Yang Tianwei Zhang Yan Gan Tao Xiang Yang Liu FedML 31 9 0 19 Dec 2021
Applying the Shuffle Model of Differential Privacy to Vector Aggregation Mary Scott Graham Cormode Carsten Maple FedML 18 3 0 10 Dec 2021
Optimal Compression of Locally Differentially Private Mechanisms Abhin Shah Wei-Ning Chen Johannes Ballé Peter Kairouz Lucas Theis 35 42 0 29 Oct 2021
DFL: High-Performance Blockchain-Based Federated Learning Yongding Tian Zhuoran Guo Jiaxuan Zhang Zaid Al-Ars OOD FedML 29 10 0 28 Oct 2021
On the Privacy Risks of Deploying Recurrent Neural Networks in Machine Learning Models Yunhao Yang Parham Gohari Ufuk Topcu AAML 30 3 0 06 Oct 2021
Enforcing fairness in private federated learning via the modified method of differential multipliers Borja Rodríguez Gálvez Filip Granqvist Rogier van Dalen M. Seigel FedML 48 52 0 17 Sep 2021
Source Inference Attacks in Federated Learning Hongsheng Hu Z. Salcic Lichao Sun Gillian Dobbie Xuyun Zhang 27 79 0 13 Sep 2021
FedTriNet: A Pseudo Labeling Method with Three Players for Federated Semi-supervised Learning Liwei Che Zewei Long Jiaqi Wang Yaqing Wang Houping Xiao Fenglong Ma FedML 27 23 0 12 Sep 2021
FedCon: A Contrastive Framework for Federated Semi-Supervised Learning Zewei Long Jiaqi Wang Yaqing Wang Houping Xiao Fenglong Ma FedML 48 22 0 09 Sep 2021
Federated Learning Versus Classical Machine Learning: A Convergence Comparison Muhammad Asad Ahmed Moustafa Takayuki Ito FedML 30 42 0 22 Jul 2021
Learner-Private Convex Optimization Jiaming Xu Kuang Xu Dana Yang FedML 19 2 0 23 Feb 2021
Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications Matthias Paulik M. Seigel Henry Mason Dominic Telaar Joris Kluivers ... Dominic Hughes O. Javidbakht Fei Dong Rehan Rishi Stanley Hung FedML 183 126 0 16 Feb 2021
Achieving Security and Privacy in Federated Learning Systems: Survey, Research Challenges and Future Directions Alberto Blanco-Justicia J. Domingo-Ferrer Sergio Martínez David Sánchez Adrian Flanagan K. E. Tan FedML 26 110 0 12 Dec 2020
Design and Analysis of Uplink and Downlink Communications for Federated Learning Sihui Zheng Cong Shen Xiang Chen 39 140 0 07 Dec 2020
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 183 355 0 07 Dec 2020
Federated Model Distillation with Noise-Free Differential Privacy Lichao Sun Lingjuan Lyu FedML 29 106 0 11 Sep 2020