Differential Privacy By Sampling
Cryptography and Security
2017-08-08 v1
Abstract
In this paper we present the Sampling Privacy mechanism for privately releasing personal data. Sampling Privacy is a sampling based privacy mechanism that satisfies differential privacy.
Cite
@article{arxiv.1708.01884,
title = {Differential Privacy By Sampling},
author = {Josh Joy and Mario Gerla},
journal= {arXiv preprint arXiv:1708.01884},
year = {2017}
}
Related papers
View all related →
Cryptography and Security · Computer Science
Distributed Differential Privacy By Sampling
Joshua Joy
2017-06-16
Machine Learning · Computer Science
Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences
Borja Balle, Gilles Barthe, Marco Gaboardi
2018-11-26
Machine Learning · Statistics
Bayesian Differential Privacy through Posterior Sampling
Christos Dimitrakakis, Blaine Nelson, and Zuhe Zhang, Aikaterini Mitrokotsa +1
2016-12-26
Cryptography and Security · Computer Science
On Sampling, Anonymization, and Differential Privacy: Or, k-Anonymization Meets Differential Privacy
Ninghui Li, Wahbeh Qardaji, Dong Su
2015-03-17
Methodology · Statistics
Controlling Privacy Loss in Sampling Schemes: an Analysis of Stratified and Cluster Sampling
Mark Bun, Jörg Drechsler, Marco Gaboardi, Audra McMillan +1
2023-06-23
Cryptography and Security · Computer Science
Composition of Differential Privacy & Privacy Amplification by Subsampling
Thomas Steinke
2022-10-27
Cryptography and Security · Computer Science
Improving Statistical Privacy by Subsampling
Dennis Breutigam, Rüdiger Reischuk
2025-04-16
Machine Learning · Statistics
Integral Privacy for Sampling
Hisham Husain, Zac Cranko, Richard Nock
2019-07-04
Machine Learning · Computer Science
Pain-Free Random Differential Privacy with Sensitivity Sampling
Benjamin I. P. Rubinstein, Francesco Aldà
2017-06-12
Cryptography and Security · Computer Science
On the Benefits of Sampling in Privacy Preserving Statistical Analysis on Distributed Databases
Bing-Rong Lin, Ye Wang, Shantanu Rane
2013-04-18
Cryptography and Security · Computer Science
Learning With Differential Privacy
Poushali Sengupta, Sudipta Paul, Subhankar Mishra
2020-06-12
Optimization and Control · Mathematics
Differentially Private Filtering
Jerome Le Ny, George J. Pappas
2012-09-12
Statistics Theory · Mathematics
A statistical framework for differential privacy
Larry Wasserman, Shuheng Zhou
2012-01-11
Cryptography and Security · Computer Science
Causal Discovery Under Local Privacy
Rūta Binkytė, Carlos Pinzón, Szilvia Lestyán, Kangsoo Jung +2
2024-05-06
Cryptography and Security · Computer Science
Efficient, Differentially Private Point Estimators
Adam Smith
2008-09-30
Optimization and Control · Mathematics
Bayesian Differential Privacy for Linear Dynamical Systems
Genki Sugiura, Kaito Ito, Kenji Kashima
2021-06-25
Cryptography and Security · Computer Science
Differential Privacy: on the trade-off between Utility and Information Leakage
Mário S. Alvim, Miguel E. Andrés, Konstantinos Chatzikokolakis, Pierpaolo Degano +1
2014-06-18
Cryptography and Security · Computer Science
Personalized Privacy Amplification via Importance Sampling
Dominik Fay, Sebastian Mair, Jens Sjölund
2025-03-31
Machine Learning · Computer Science
Tangent differential privacy
Lexing Ying
2024-06-14
Cryptography and Security · Computer Science
Private sampling: a noiseless approach for generating differentially private synthetic data
March Boedihardjo, Thomas Strohmer, Roman Vershynin
2022-06-06
Cryptography and Security · Computer Science
The Adverse Effects of Omitting Records in Differential Privacy: How Sampling and Suppression Degrade the Privacy--Utility Tradeoff (Long Version)
Àlex Miranda-Pascual, Javier Parra-Arnau, Thorsten Strufe
2026-01-23
Cryptography and Security · Computer Science
Randomized Privacy Budget Differential Privacy
Meisam Mohammady
2022-09-07
Databases · Computer Science
Differential Privacy: An Economic Method for Choosing Epsilon
Justin Hsu, Marco Gaboardi, Andreas Haeberlen, Sanjeev Khanna +3
2018-03-16
Methodology · Statistics
Transparent Privacy is Principled Privacy
Ruobin Gong
2022-09-20
Machine Learning · Computer Science
Statistical Privacy Guarantees of Machine Learning Preprocessing Techniques
Ashly Lau, Jonathan Passerat-Palmbach
2021-09-07