Distributed Differential Privacy via Shuffling

4 August 2018

Papers citing "Distributed Differential Privacy via Shuffling"

50 / 191 papers shown

Title
On Differentially Private Federated Linear Contextual Bandits Xingyu Zhou Sayak Ray Chowdhury FedML 43 15 0 27 Feb 2023
Multi-Message Shuffled Privacy in Federated Learning Antonious M. Girgis Suhas Diggavi FedML 28 8 0 22 Feb 2023
Concurrent Shuffle Differential Privacy Under Continual Observation J. Tenenbaum Haim Kaplan Yishay Mansour Uri Stemmer FedML 33 2 0 29 Jan 2023
(Private) Kernelized Bandits with Distributed Biased Feedback Fengjiao Li Xingyu Zhou Bo Ji 33 5 0 28 Jan 2023
Differentially Private Natural Language Models: Recent Advances and Future Directions Lijie Hu Ivan Habernal Lei Shen Di Wang AAML 30 18 0 22 Jan 2023
Simple Binary Hypothesis Testing under Local Differential Privacy and Communication Constraints Ankit Pensia Amir-Reza Asadi Varun Jog Po-Ling Loh 25 12 0 09 Jan 2023
Skellam Mixture Mechanism: a Novel Approach to Federated Learning with Differential Privacy Ergute Bao Yizheng Zhu X. Xiao Yifan Yang Beng Chin Ooi B. Tan Khin Mi Mi Aung FedML 31 19 0 08 Dec 2022
Lemmas of Differential Privacy Yiyang Huang C. Canonne 37 1 0 21 Nov 2022
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 27 6 0 18 Nov 2022
Discrete Distribution Estimation under User-level Local Differential Privacy Jayadev Acharya Yuhan Liu Ziteng Sun 35 16 0 07 Nov 2022
Anonymized Histograms in Intermediate Privacy Models Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi PICV 115 1 0 27 Oct 2022
PAC Privacy: Automatic Privacy Measurement and Control of Data Processing Hanshen Xiao S. Devadas 26 11 0 07 Oct 2022
Composition of Differential Privacy & Privacy Amplification by Subsampling Thomas Steinke 64 50 0 02 Oct 2022
Dordis: Efficient Federated Learning with Dropout-Resilient Differential Privacy Zhifeng Jiang Wei Wang Ruichuan Chen 43 7 0 26 Sep 2022
Differentially private partitioned variational inference Mikko A. Heikkilä Matthew Ashman S. Swaroop Richard Turner Antti Honkela FedML 30 2 0 23 Sep 2022
Private Stochastic Optimization With Large Worst-Case Lipschitz Parameter: Optimal Rates for (Non-Smooth) Convex Losses and Extension to Non-Convex Losses Andrew Lowy Meisam Razaviyayn 30 13 0 15 Sep 2022
Algorithms with More Granular Differential Privacy Guarantees Badih Ghazi Ravi Kumar Pasin Manurangsi Thomas Steinke 62 6 0 08 Sep 2022
DPAUC: Differentially Private AUC Computation in Federated Learning Jiankai Sun Xin Yang Yuanshun Yao Junyuan Xie Di Wu Chong-Jun Wang FedML 50 11 0 25 Aug 2022
Necessary Conditions in Multi-Server Differential Privacy Albert Cheu Chao Yan 26 8 0 17 Aug 2022
Stronger Privacy Amplification by Shuffling for Rényi and Approximate Differential Privacy Vitaly Feldman Audra McMillan Kunal Talwar FedML 29 47 0 09 Aug 2022
Fine-grained Private Knowledge Distillation Yuntong Li Shaowei Wang Yingying Wang Jin Li Yuqiu Qian Bangzhou Xin Wei Yang 23 0 0 27 Jul 2022
Differentially Private Linear Bandits with Partial Distributed Feedback Fengjiao Li Xingyu Zhou Bo Ji FedML 34 13 0 12 Jul 2022
MPC for Tech Giants (GMPC): Enabling Gulliver and the Lilliputians to Cooperate Amicably Bar Alon M. Naor Eran Omri Uri Stemmer 24 5 0 11 Jul 2022
The Poisson binomial mechanism for secure and private federated learning Wei-Ning Chen Ayfer Özgür Peter Kairouz FedML 16 2 0 09 Jul 2022
Differentially Private Stochastic Linear Bandits: (Almost) for Free Osama A. Hanna Antonious M. Girgis Christina Fragouli Suhas Diggavi FedML 27 18 0 07 Jul 2022
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression Zhize Li Haoyu Zhao Boyue Li Yuejie Chi FedML 35 41 0 20 Jun 2022
Shuffle Gaussian Mechanism for Differential Privacy Seng Pei Liew Tsubasa Takahashi FedML 29 2 0 20 Jun 2022
Walking to Hide: Privacy Amplification via Random Message Exchanges in Network Hao Wu O. Ohrimenko Anthony Wirth FedML 25 1 0 20 Jun 2022
On Privacy and Personalization in Cross-Silo Federated Learning Ziyu Liu Shengyuan Hu Zhiwei Steven Wu Virginia Smith FedML 22 52 0 16 Jun 2022
Distributed Differential Privacy in Multi-Armed Bandits Sayak Ray Chowdhury Xingyu Zhou 27 12 0 12 Jun 2022
Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging Edwige Cyffers Mathieu Even A. Bellet Laurent Massoulié FedML 6 23 0 10 Jun 2022
Group privacy for personalized federated learning Filippo Galli Sayan Biswas Kangsoo Jung Tommaso Cucinotta C. Palamidessi FedML 15 12 0 07 Jun 2022
Privacy Amplification via Shuffled Check-Ins Seng Pei Liew Satoshi Hasegawa Tsubasa Takahashi FedML 32 0 0 07 Jun 2022
Differentially Private AUC Computation in Vertical Federated Learning Jiankai Sun Xin Yang Yuanshun Yao Junyuan Xie Di Wu Chong-Jun Wang FedML 56 5 0 24 May 2022
Tight Differential Privacy Guarantees for the Shuffle Model with $k$ -Randomized Response Sayan Biswas Kangsoo Jung C. Palamidessi 8 0 0 18 May 2022
Improved Utility Analysis of Private CountSketch Rasmus Pagh M. Thorup FedML 34 20 0 17 May 2022
Tight Differential Privacy Blanket for Shuffle Model Sayan Biswas Kangsoo Jung C. Palamidessi 23 0 0 09 May 2022
Network Gradient Descent Algorithm for Decentralized Federated Learning Shuyuan Wu Danyang Huang Hansheng Wang FedML 30 11 0 06 May 2022
Optimal Algorithms for Mean Estimation under Local Differential Privacy Hilal Asi Vitaly Feldman Kunal Talwar 40 41 0 05 May 2022
Differentially Private Triangle and 4-Cycle Counting in the Shuffle Model Jacob Imola Takao Murakami Kamalika Chaudhuri 27 23 0 03 May 2022
Private Non-Convex Federated Learning Without a Trusted Server Andrew Lowy Ali Ghafelebashi Meisam Razaviyayn FedML 36 24 0 13 Mar 2022
Differential Privacy Amplification in Quantum and Quantum-inspired Algorithms Armando Angrisani Mina Doosti E. Kashefi 24 12 0 07 Mar 2022
Label Leakage and Protection from Forward Embedding in Vertical Federated Learning Jiankai Sun Xin Yang Yuanshun Yao Chong-Jun Wang FedML 36 37 0 02 Mar 2022
Private Frequency Estimation via Projective Geometry Vitaly Feldman Jelani Nelson Huy Le Nguyen Kunal Talwar 36 21 0 01 Mar 2022
Differential Secrecy for Distributed Data and Applications to Robust Differentially Secure Vector Summation Kunal Talwar FedML 35 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 21 13 0 21 Feb 2022
Shuffle Private Linear Contextual Bandits Sayak Ray Chowdhury Xingyu Zhou FedML 26 25 0 11 Feb 2022
Distributed Differentially Private Ranking Aggregation Baobao Song Qiujun Lan Yang Li Gang Li FedML 18 3 0 07 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
Statistical anonymity: Quantifying reidentification risks without reidentifying users Gecia Bravo Hermsdorff R. Busa-Fekete L. Gunderson Andrés Munoz Medina Umar Syed 13 1 0 28 Jan 2022