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The Privacy Blanket of the Shuffle Model

7 March 2019

Papers citing "The Privacy Blanket of the Shuffle Model"

50 / 90 papers shown

Title
Locally Differentially Private Frequency Estimation via Joint Randomized Response Ye Zheng Shafizur Rahman Seeam Yidan Hu Rui Zhang Yanchao Zhang 64 0 0 15 May 2025
PREAMBLE: Private and Efficient Aggregation of Block Sparse Vectors and Applications Hilal Asi Vitaly Feldman Hannah Keller G. Rothblum Kunal Talwar FedML 117 1 0 14 Mar 2025
On the Robustness of LDP Protocols for Numerical Attributes under Data Poisoning Attacks Xiaoguang Li Zitao Li Ninghui Li Wenhai Sun AAML 145 4 0 28 Jan 2025
Segmented Private Data Aggregation in the Multi-message Shuffle Model Shaowei Wang Hongqiao Chen Sufen Zeng Ruilin Yang Hui Jiang ... Kaiqi Yu Rundong Mei Shaozheng Huang Wei Yang Bangzhou Xin FedML 128 0 0 31 Dec 2024
Nebula: Efficient, Private and Accurate Histogram Estimation Ali Shahin Shamsabadi Peter Snyder Ralph Giles A. Bellet Hamed Haddadi 56 0 0 15 Sep 2024
Differentially Private Block-wise Gradient Shuffle for Deep Learning Zilong Zhang FedML 106 0 0 31 Jul 2024
Efficient Verifiable Differential Privacy with Input Authenticity in the Local and Shuffle Model Tariq Bontekoe Hassan Jameel Asghar Fatih Turkmen 49 2 0 27 Jun 2024
Beyond Statistical Estimation: Differentially Private Individual Computation via Shuffling Shaowei Wang Changyu Dong Xiangfu Song Jin Li Zhili Zhou Di Wang Han Wu 114 0 0 26 Jun 2024
RASE: Efficient Privacy-preserving Data Aggregation against Disclosure Attacks for IoTs Zuyan Wang Jun Tao Dikai Zou 40 0 0 31 May 2024
FastLloyd: Federated, Accurate, Secure, and Tunable $k$ -Means Clustering with Differential Privacy Abdulrahman Diaa Thomas Humphries Florian Kerschbaum FedML 108 0 0 03 May 2024
A Generalized Shuffle Framework for Privacy Amplification: Strengthening Privacy Guarantees and Enhancing Utility E. Chen Yang Cao Yifei Ge FedML 69 8 0 22 Dec 2023
Practical, Private Assurance of the Value of Collaboration Hassan Jameel Asghar Zhigang Lu Zhongrui Zhao Dali Kaafar FedML 64 0 0 04 Oct 2023
Differentially Private Aggregation via Imperfect Shuffling Badih Ghazi Ravi Kumar Pasin Manurangsi Jelani Nelson Samson Zhou FedML 109 1 0 28 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 161 14 0 27 Jul 2023
Analyzing the Shuffle Model through the Lens of Quantitative Information Flow Mireya Jurado Ramon G. Gonze Mário S. Alvim C. Palamidessi 66 1 0 22 May 2023
Private Federated Statistics in an Interactive Setting Audra McMillan O. Javidbakht Kunal Talwar Elliot Briggs Mike Chatzidakis ... Paul J. Pelzl Rehan Rishi Congzheng Song Shan Wang Shundong Zhou FedML 87 6 0 18 Nov 2022
Composition of Differential Privacy & Privacy Amplification by Subsampling Thomas Steinke 166 54 0 02 Oct 2022
Private Read Update Write (PRUW) in Federated Submodel Learning (FSL): Communication Efficient Schemes With and Without Sparsification Sajani Vithana S. Ulukus FedML 77 20 0 09 Sep 2022
FedPerm: Private and Robust Federated Learning by Parameter Permutation Hamid Mozaffari Virendra J. Marathe D. Dice FedML 85 4 0 16 Aug 2022
How Much Privacy Does Federated Learning with Secure Aggregation Guarantee? A. Elkordy Jiang Zhang Yahya H. Ezzeldin Konstantinos Psounis A. Avestimehr FedML 72 38 0 03 Aug 2022
Differentially Private Stochastic Linear Bandits: (Almost) for Free Osama A. Hanna Antonious M. Girgis Christina Fragouli Suhas Diggavi FedML 80 18 0 07 Jul 2022
"You Can't Fix What You Can't Measure": Privately Measuring Demographic Performance Disparities in Federated Learning Marc Juárez Aleksandra Korolova FedML 79 10 0 24 Jun 2022
Walking to Hide: Privacy Amplification via Random Message Exchanges in Network Hao Wu O. Ohrimenko Anthony Wirth FedML 54 1 0 20 Jun 2022
Distributed Differential Privacy in Multi-Armed Bandits Sayak Ray Chowdhury Xingyu Zhou 97 13 0 12 Jun 2022
Group privacy for personalized federated learning Filippo Galli Sayan Biswas Kangsoo Jung Tommaso Cucinotta C. Palamidessi FedML 77 12 0 07 Jun 2022
Impact of Sampling on Locally Differentially Private Data Collection Sayan Biswas Graham Cormode Carsten Maple FedML 74 0 0 02 Jun 2022
Private Federated Submodel Learning with Sparsification Sajani Vithana S. Ulukus FedML 70 10 0 31 May 2022
Tight Differential Privacy Blanket for Shuffle Model Sayan Biswas Kangsoo Jung C. Palamidessi 36 0 0 09 May 2022
Optimal Algorithms for Mean Estimation under Local Differential Privacy Hilal Asi Vitaly Feldman Kunal Talwar 100 42 0 05 May 2022
Privacy-Aware Compression for Federated Data Analysis Kamalika Chaudhuri Chuan Guo Michael G. Rabbat FedML 75 27 0 15 Mar 2022
The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning Wei-Ning Chen Christopher A. Choquette-Choo Peter Kairouz A. Suresh FedML 118 65 0 07 Mar 2022
Private Frequency Estimation via Projective Geometry Vitaly Feldman Jelani Nelson Huy Le Nguyen Kunal Talwar 96 21 0 01 Mar 2022
Differentially Private Speaker Anonymization Ali Shahin Shamsabadi B. M. L. Srivastava A. Bellet Nathalie Vauquier Emmanuel Vincent Mohamed Maouche Marc Tommasi Nicolas Papernot MIACV 148 35 0 23 Feb 2022
Using Illustrations to Communicate Differential Privacy Trust Models: An Investigation of Users' Comprehension, Perception, and Data Sharing Decision Aiping Xiong Chuhao Wu Tianhao Wang R. Proctor Jeremiah Blocki Ninghui Li S. Jha 60 13 0 21 Feb 2022
Shuffle Private Linear Contextual Bandits Sayak Ray Chowdhury Xingyu Zhou FedML 98 27 0 11 Feb 2022
Aggregation and Transformation of Vector-Valued Messages in the Shuffle Model of Differential Privacy Mary Scott Graham Cormode Carsten Maple 85 11 0 31 Jan 2022
Mitigating Leakage from Data Dependent Communications in Decentralized Computing using Differential Privacy Riad Ladjel N. Anciaux A. Bellet Guillaume Scerri FedML 116 0 0 23 Dec 2021
Privacy Amplification via Shuffling for Linear Contextual Bandits Evrard Garcelon Kamalika Chaudhuri Vianney Perchet Matteo Pirotta FedML 111 20 0 11 Dec 2021
Differentially Private Exploration in Reinforcement Learning with Linear Representation Paul Luyo Evrard Garcelon A. Lazaric Matteo Pirotta 139 11 0 02 Dec 2021
Differentially Private Federated Learning on Heterogeneous Data Maxence Noble A. Bellet Aymeric Dieuleveut FedML 86 110 0 17 Nov 2021
Optimal Compression of Locally Differentially Private Mechanisms Abhin Shah Wei-Ning Chen Johannes Ballé Peter Kairouz Lucas Theis 91 42 0 29 Oct 2021
Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message Badih Ghazi Ravi Kumar Pasin Manurangsi Rasmus Pagh Amer Sinha FedML 132 38 0 27 Sep 2021
Random Sampling Plus Fake Data: Multidimensional Frequency Estimates With Local Differential Privacy Héber H. Arcolezi Jean-François Couchot Bechara al Bouna Xiaokui Xiao 53 27 0 15 Sep 2021
Private Retrieval, Computing and Learning: Recent Progress and Future Challenges S. Ulukus Salman Avestimehr Michael C. Gastpar S. Jafar Ravi Tandon Chao Tian FedML 116 69 0 30 Jul 2021
Renyi Differential Privacy of the Subsampled Shuffle Model in Distributed Learning Antonious M. Girgis Deepesh Data Suhas Diggavi FedML 74 22 0 19 Jul 2021
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 279 422 0 14 Jul 2021
Asymptotically Optimal Locally Private Heavy Hitters via Parameterized Sketches Hao Wu Anthony Wirth FedML 45 5 0 15 Jun 2021
Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead Badih Ghazi Ravi Kumar Pasin Manurangsi Rasmus Pagh FedML 99 51 0 08 Jun 2021
Differentially Private Multi-Armed Bandits in the Shuffle Model J. Tenenbaum Haim Kaplan Yishay Mansour Uri Stemmer FedML 89 29 0 05 Jun 2021
Tight Accounting in the Shuffle Model of Differential Privacy A. Koskela Mikko A. Heikkilä Antti Honkela FedML 65 17 0 01 Jun 2021