Tight Differential Privacy Guarantees for the Shuffle Model with
$k$-Randomized Response

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Tight Differential Privacy Guarantees for the Shuffle Model with $k$ -Randomized Response

18 May 2022

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Papers citing "Tight Differential Privacy Guarantees for the Shuffle Model with $k$-Randomized Response"

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Title
Tight Accounting in the Shuffle Model of Differential Privacy A. Koskela Mikko A. Heikkilä Antti Honkela FedML 49 17 0 01 Jun 2021
Differentially Private Histograms in the Shuffle Model from Fake Users Albert Cheu M. Zhilyaev FedML 100 28 0 06 Apr 2021
Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling Vitaly Feldman Audra McMillan Kunal Talwar FedML 81 162 0 23 Dec 2020
Tight Differential Privacy for Discrete-Valued Mechanisms and for the Subsampled Gaussian Mechanism Using FFT A. Koskela Hibiki Ito Lukas Prediger Antti Honkela 48 59 0 12 Jun 2020
Connecting Robust Shuffle Privacy and Pan-Privacy Victor Balcer Albert Cheu Matthew Joseph Jieming Mao FedML 90 42 0 20 Apr 2020
Encode, Shuffle, Analyze Privacy Revisited: Formalizations and Empirical Evaluation Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Shuang Song Kunal Talwar Abhradeep Thakurta 72 84 0 10 Jan 2020
Separating Local & Shuffled Differential Privacy via Histograms Victor Balcer Albert Cheu FedML 113 68 0 15 Nov 2019
Differentially Private Summation with Multi-Message Shuffling Borja Balle James Bell Adria Gascon Kobbi Nissim FedML 88 47 0 20 Jun 2019
Scalable and Differentially Private Distributed Aggregation in the Shuffled Model Badih Ghazi Rasmus Pagh A. Velingker FedML 80 98 0 19 Jun 2019
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 203 430 0 29 Nov 2018
Distributed Differential Privacy via Shuffling Albert Cheu Adam D. Smith Jonathan R. Ullman David Zeber M. Zhilyaev FedML 99 352 0 04 Aug 2018
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising Borja Balle Yu Wang MLT 97 413 0 16 May 2018
Prochlo: Strong Privacy for Analytics in the Crowd Andrea Bittau Ulfar Erlingsson Petros Maniatis Ilya Mironov A. Raghunathan David Lie Mitch Rudominer Ushasree Kode J. Tinnés B. Seefeld 151 279 0 02 Oct 2017
Discrete Distribution Estimation under Local Privacy Peter Kairouz Kallista A. Bonawitz Daniel Ramage 77 330 0 24 Feb 2016