A Generalized Shuffle Framework for Privacy Amplification: Strengthening
Privacy Guarantees and Enhancing Utility

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A Generalized Shuffle Framework for Privacy Amplification: Strengthening Privacy Guarantees and Enhancing Utility

22 December 2023

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Papers citing "A Generalized Shuffle Framework for Privacy Amplification: Strengthening Privacy Guarantees and Enhancing Utility"

6 / 6 papers shown

Title
Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling Vitaly Feldman Audra McMillan Kunal Talwar FedML 84 162 0 23 Dec 2020
FLAME: Differentially Private Federated Learning in the Shuffle Model Ruixuan Liu Yang Cao Hong Chen Ruoyang Guo Masatoshi Yoshikawa FedML 83 96 0 17 Sep 2020
The Privacy Blanket of the Shuffle Model Borja Balle James Bell Adria Gascon Kobbi Nissim FedML 77 238 0 07 Mar 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 109 352 0 04 Aug 2018
The Composition Theorem for Differential Privacy Peter Kairouz Sewoong Oh Pramod Viswanath 168 685 0 04 Nov 2013