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Pure differential privacy for rectangle queries via private partitions

Cynthia Dwork, Moni Naor, Omer Reingold, Guy N. Rothblum

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We consider the task of data analysis with pure differential privacy. We construct new and improved mechanisms for statistical release of interval and rectangle queries. We also obtain a new algorithm for counting over a data stream under continual observation, whose error has optimal dependence on the data stream’s length. A central ingredient in all of these result is a differentially private partition mechanism. Given set of data items drawn from a large universe, this mechanism outputs a partition of the universe into a small number of segments, each of which contain only a few of the data items.

Original languageEnglish
Title of host publicationAdvances in Cryptology – ASIACRYPT 2015 - 21st International Conference on the Theory and Application of Cryptology and Information Security, Proceedings
EditorsTetsu Iwata, Jung Hee Cheon
PublisherSpringer Verlag
Pages735-751
Number of pages17
ISBN (Print)9783662487990
DOIs
StatePublished - 2015
Event21st International Conference on the Theory and Application of Cryptology and Information Security, ASIACRYPT 2015 - Auckland, New Zealand
Duration: 29 Nov 20153 Dec 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9453

Conference

Conference21st International Conference on the Theory and Application of Cryptology and Information Security, ASIACRYPT 2015
Country/TerritoryNew Zealand
CityAuckland
Period29/11/153/12/15

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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