The Privacy Blanket of the Shuffle Model

7 March 2019

Papers citing "The Privacy Blanket of the Shuffle Model"

50 / 142 papers shown

Title
Distributed Differential Privacy in Multi-Armed Bandits Sayak Ray Chowdhury Xingyu Zhou 25 12 0 12 Jun 2022
Group privacy for personalized federated learning Filippo Galli Sayan Biswas Kangsoo Jung Tommaso Cucinotta C. Palamidessi FedML 13 12 0 07 Jun 2022
Impact of Sampling on Locally Differentially Private Data Collection Sayan Biswas Graham Cormode Carsten Maple FedML 22 0 0 02 Jun 2022
Private Federated Submodel Learning with Sparsification Sajani Vithana S. Ulukus FedML 24 10 0 31 May 2022
Tight Differential Privacy Guarantees for the Shuffle Model with $k$ -Randomized Response Sayan Biswas Kangsoo Jung C. Palamidessi 6 0 0 18 May 2022
Tight Differential Privacy Blanket for Shuffle Model Sayan Biswas Kangsoo Jung C. Palamidessi 13 0 0 09 May 2022
Optimal Algorithms for Mean Estimation under Local Differential Privacy Hilal Asi Vitaly Feldman Kunal Talwar 22 41 0 05 May 2022
Differentially Private Triangle and 4-Cycle Counting in the Shuffle Model Jacob Imola Takao Murakami Kamalika Chaudhuri 14 22 0 03 May 2022
Privacy-Aware Compression for Federated Data Analysis Kamalika Chaudhuri Chuan Guo Michael G. Rabbat FedML 25 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 31 63 0 07 Mar 2022
Private Frequency Estimation via Projective Geometry Vitaly Feldman Jelani Nelson Huy Le Nguyen Kunal Talwar 28 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 38 32 0 23 Feb 2022
Differential Secrecy for Distributed Data and Applications to Robust Differentially Secure Vector Summation Kunal Talwar FedML 23 10 0 22 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 11 13 0 21 Feb 2022
Nonparametric extensions of randomized response for private confidence sets Ian Waudby-Smith Zhiwei Steven Wu Aaditya Ramdas 12 9 0 17 Feb 2022
OLIVE: Oblivious Federated Learning on Trusted Execution Environment against the risk of sparsification Fumiyuki Kato Yang Cao Masatoshi Yoshikawa FedML 19 5 0 15 Feb 2022
Shuffle Private Linear Contextual Bandits Sayak Ray Chowdhury Xingyu Zhou FedML 16 25 0 11 Feb 2022
Aggregation and Transformation of Vector-Valued Messages in the Shuffle Model of Differential Privacy Mary Scott Graham Cormode Carsten Maple 35 11 0 31 Jan 2022
Transfer Learning In Differential Privacy's Hybrid-Model Reʾuven Kohen Or Sheffet 21 6 0 28 Jan 2022
Mitigating Leakage from Data Dependent Communications in Decentralized Computing using Differential Privacy Riad Ladjel N. Anciaux A. Bellet Guillaume Scerri FedML 26 0 0 23 Dec 2021
Pure Differential Privacy from Secure Intermediaries Albert Cheu Chao Yan FedML 12 9 0 19 Dec 2021
Privacy Amplification via Shuffling for Linear Contextual Bandits Evrard Garcelon Kamalika Chaudhuri Vianney Perchet Matteo Pirotta FedML 22 18 0 11 Dec 2021
Applying the Shuffle Model of Differential Privacy to Vector Aggregation Mary Scott Graham Cormode Carsten Maple FedML 14 3 0 10 Dec 2021
Differentially Private Exploration in Reinforcement Learning with Linear Representation Paul Luyo Evrard Garcelon A. Lazaric Matteo Pirotta 32 11 0 02 Dec 2021
Differentially Private Federated Learning on Heterogeneous Data Maxence Noble A. Bellet Aymeric Dieuleveut FedML 11 102 0 17 Nov 2021
Frequency Estimation in the Shuffle Model with Almost a Single Message Qiyao Luo Yilei Wang K. Yi FedML 30 11 0 12 Nov 2021
Towards Sparse Federated Analytics: Location Heatmaps under Distributed Differential Privacy with Secure Aggregation Eugene Bagdasaryan Peter Kairouz S. Mellem Adria Gascon Kallista A. Bonawitz D. Estrin Marco Gruteser 14 28 0 03 Nov 2021
Optimal Compression of Locally Differentially Private Mechanisms Abhin Shah Wei-Ning Chen Johannes Ballé Peter Kairouz Lucas Theis 16 42 0 29 Oct 2021
PRECAD: Privacy-Preserving and Robust Federated Learning via Crypto-Aided Differential Privacy Xiaolan Gu Ming Li Lishuang Xiong FedML 6 10 0 22 Oct 2021
Infinitely Divisible Noise in the Low Privacy Regime Rasmus Pagh N. Stausholm FedML 25 2 0 13 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 57 36 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 15 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 20 64 0 30 Jul 2021
Selective MPC: Distributed Computation of Differentially Private Key-Value Statistics Thomas Humphries Rasoul Akhavan Mahdavi Shannon Veitch Florian Kerschbaum 12 11 0 26 Jul 2021
Differential Privacy in the Shuffle Model: A Survey of Separations Albert Cheu FedML 26 39 0 25 Jul 2021
Designing a Location Trace Anonymization Contest Takao Murakami Hiromi Arai Koki Hamada Takuma Hatano M. Iguchi ... Hidenobu Oguri Chiemi Watanabe A. Yamada Takayasu Yamaguchi Yuji Yamaoka 14 2 0 22 Jul 2021
Renyi Differential Privacy of the Subsampled Shuffle Model in Distributed Learning Antonious M. Girgis Deepesh Data Suhas Diggavi FedML 20 21 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 175 411 0 14 Jul 2021
Asymptotically Optimal Locally Private Heavy Hitters via Parameterized Sketches Hao Wu Anthony Wirth FedML 9 5 0 15 Jun 2021
A Shuffling Framework for Local Differential Privacy Casey Meehan A. Chowdhury Kamalika Chaudhuri Somesh Jha 33 0 0 11 Jun 2021
Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead Badih Ghazi Ravi Kumar Pasin Manurangsi Rasmus Pagh FedML 24 48 0 08 Jun 2021
Differentially Private Multi-Armed Bandits in the Shuffle Model J. Tenenbaum Haim Kaplan Yishay Mansour Uri Stemmer FedML 11 28 0 05 Jun 2021
Tight Accounting in the Shuffle Model of Differential Privacy A. Koskela Mikko A. Heikkilä Antti Honkela FedML 15 17 0 01 Jun 2021
Privacy Amplification Via Bernoulli Sampling Jacob Imola Kamalika Chaudhuri FedML 14 7 0 21 May 2021
On the Renyi Differential Privacy of the Shuffle Model Antonious M. Girgis Deepesh Data Suhas Diggavi A. Suresh Peter Kairouz 12 44 0 11 May 2021
Locally Private k-Means in One Round Alisa Chang Badih Ghazi Ravi Kumar Pasin Manurangsi 37 30 0 20 Apr 2021
Differentially Private Histograms in the Shuffle Model from Fake Users Albert Cheu M. Zhilyaev FedML 19 27 0 06 Apr 2021
Frequency Estimation Under Multiparty Differential Privacy: One-shot and Streaming Ziyue Huang Yuan Qiu K. Yi Graham Cormode 16 25 0 05 Apr 2021
The Sample Complexity of Distribution-Free Parity Learning in the Robust Shuffle Model Kobbi Nissim Chao Yan 20 1 0 29 Mar 2021
Lossless Compression of Efficient Private Local Randomizers Vitaly Feldman Kunal Talwar 14 40 0 24 Feb 2021