Optimal differential privacy mechanisms under Hamming distortion for structured source classes

Kousha Kalantari, Lalitha Sankar, Anand D. Sarwate

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

6 Scopus citations

Abstract

We examine a tradeoff between privacy and utility in terms of local differential privacy (L-DP) and Hamming distortion for certain classes of finite-alphabet sources under Hamming distortion. We define two classes: permutation-invariant, and ordered statistics (whose probability mass functions are monotonic). We obtain the optimal L-DP mechanism for permutation-invariant sources and derive upper and lower bounds on the achievable local differential privacy for ordered statistics for a range of target distortion values.

Original languageEnglish (US)
Title of host publicationProceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2069-2073
Number of pages5
Volume2016-August
ISBN (Electronic)9781509018062
DOIs
StatePublished - Aug 10 2016
Event2016 IEEE International Symposium on Information Theory, ISIT 2016 - Barcelona, Spain
Duration: Jul 10 2016Jul 15 2016

Other

Other2016 IEEE International Symposium on Information Theory, ISIT 2016
CountrySpain
CityBarcelona
Period7/10/167/15/16

Keywords

  • Differential Privacy
  • Information Leakage
  • utility-privacy tradeoff

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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    Kalantari, K., Sankar, L., & Sarwate, A. D. (2016). Optimal differential privacy mechanisms under Hamming distortion for structured source classes. In Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory (Vol. 2016-August, pp. 2069-2073). [7541663] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT.2016.7541663