A minimax distortion view of differentially private query release

Weina Wang, Lei Ying, Junshan Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

We devise query-set independent mechanisms for the problem of differentially private query release. Specifically, a differentially private mechanism is constructed to publish a synthetic database, and "customized" companion estimators are then derived to provide the best possible answers. Accordingly, the distortion corresponding to the best mechanism at the worst- case query, named the minimax distortion, provides a fundamental characterization. For the general class of statistical queries, by deriving asymptotically sharp upper and lower bounds, we prove that the minimax distortion is O(1/n) as the database size n goes to infinity, with the squared-error distortion measure and fixed dimension of data entries.

Original languageEnglish (US)
Title of host publicationConference Record - Asilomar Conference on Signals, Systems and Computers
PublisherIEEE Computer Society
Pages1046-1050
Number of pages5
Volume2016-February
ISBN (Print)9781467385763
DOIs
StatePublished - Feb 26 2016
Event49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States
Duration: Nov 8 2015Nov 11 2015

Other

Other49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
CountryUnited States
CityPacific Grove
Period11/8/1511/11/15

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing

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    Wang, W., Ying, L., & Zhang, J. (2016). A minimax distortion view of differentially private query release. In Conference Record - Asilomar Conference on Signals, Systems and Computers (Vol. 2016-February, pp. 1046-1050). [7421298] IEEE Computer Society. https://doi.org/10.1109/ACSSC.2015.7421298