Random Sampling Plus Fake Data: Multidimensional Frequency Estimates With Local Differential Privacy

15 September 2021

Héber H. Arcolezi

Jean-François Couchot

Bechara al Bouna

Xiaokui Xiao

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Papers citing "Random Sampling Plus Fake Data: Multidimensional Frequency Estimates With Local Differential Privacy"

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Google COVID-19 Community Mobility Reports: Anonymization Process Description (version 1.1) A. Aktay S. Bavadekar Gwen Cossoul John Davis Damien Desfontaines ... Swapnil Vispute Mia Vu G. Wellenius Brian Williams Royce J. Wilson 10 544 0 08 Apr 2020
LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale Ryan M. Rogers S. Subramaniam Sean Peng D. Durfee Seunghyun Lee Santosh Kumar Kancha Shraddha Sahay P. Ahammad 30 78 0 14 Feb 2020
Encode, Shuffle, Analyze Privacy Revisited: Formalizations and Empirical Evaluation Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Shuang Song Kunal Talwar Abhradeep Thakurta 55 84 0 10 Jan 2020
Estimating Numerical Distributions under Local Differential Privacy Zitao Li Tianhao Wang Milan Lopuhaä-Zwakenberg B. Škorić Ninghui Li 34 87 0 02 Dec 2019
Collecting and Analyzing Multidimensional Data with Local Differential Privacy Ning Wang Xiaokui Xiao Yifan Yang Jun Zhao S. Hui Hyejin Shin Junbum Shin Ge Yu 22 319 0 28 Jun 2019
Locally Differentially Private Frequency Estimation with Consistency Tianhao Wang Milan Lopuhaä-Zwakenberg Zitao Li B. Škorić Ninghui Li 41 76 0 20 May 2019
The Privacy Blanket of the Shuffle Model Borja Balle James Bell Adria Gascon Kobbi Nissim FedML 59 237 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 167 423 0 29 Nov 2018
Privacy Amplification by Iteration Vitaly Feldman Ilya Mironov Kunal Talwar Abhradeep Thakurta FedML 45 171 0 20 Aug 2018
Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences Borja Balle Gilles Barthe Marco Gaboardi 64 382 0 04 Jul 2018
Hadamard Response: Estimating Distributions Privately, Efficiently, and with Little Communication Jayadev Acharya Ziteng Sun Huanyu Zhang 38 148 0 13 Feb 2018
Collecting Telemetry Data Privately Bolin Ding Janardhan Kulkarni Sergey Yekhanin 40 676 0 05 Dec 2017
Locally Differentially Private Heavy Hitter Identification Tianhao Wang Ninghui Li S. Jha 20 117 0 22 Aug 2017
Minimax Optimal Procedures for Locally Private Estimation John C. Duchi Martin J. Wainwright Michael I. Jordan 63 431 0 08 Apr 2016
Discrete Distribution Estimation under Local Privacy Peter Kairouz Kallista A. Bonawitz Daniel Ramage 22 327 0 24 Feb 2016
Local, Private, Efficient Protocols for Succinct Histograms Raef Bassily Adam D. Smith FedML 40 456 0 18 Apr 2015
Building a RAPPOR with the Unknown: Privacy-Preserving Learning of Associations and Data Dictionaries Giulia Fanti Vasyl Pihur Ulfar Erlingsson 32 298 0 04 Mar 2015
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response Ulfar Erlingsson Vasyl Pihur Aleksandra Korolova 54 1,977 0 25 Jul 2014
On Sampling, Anonymization, and Differential Privacy: Or, k-Anonymization Meets Differential Privacy Ninghui Li Wahbeh H. Qardaji D. Su 62 277 0 13 Jan 2011
What Can We Learn Privately? S. Kasiviswanathan Homin K. Lee Kobbi Nissim Sofya Raskhodnikova Adam D. Smith 95 1,459 0 06 Mar 2008