Optimal differential privacy mechanisms under Hamming distortion for structured source classes

Kousha Kalantari; Lalitha Sankar; Anand D. Sarwate

doi:10.1109/ISIT.2016.7541663

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 proceeding › Conference contribution

8 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 language	English (US)
Title of host publication	Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2069-2073
Number of pages	5
ISBN (Electronic)	9781509018062
DOIs	https://doi.org/10.1109/ISIT.2016.7541663
State	Published - Aug 10 2016
Event	2016 IEEE International Symposium on Information Theory, ISIT 2016 - Barcelona, Spain Duration: Jul 10 2016 → Jul 15 2016

Publication series

Name	IEEE International Symposium on Information Theory - Proceedings
Volume	2016-August
ISSN (Print)	2157-8095

Other

Other	2016 IEEE International Symposium on Information Theory, ISIT 2016
Country/Territory	Spain
City	Barcelona
Period	7/10/16 → 7/15/16

Keywords

Differential Privacy
Information Leakage
utility-privacy tradeoff

ASJC Scopus subject areas

Theoretical Computer Science
Information Systems
Modeling and Simulation
Applied Mathematics

Access to Document

10.1109/ISIT.2016.7541663

Cite this

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 (pp. 2069-2073). [7541663] (IEEE International Symposium on Information Theory - Proceedings; Vol. 2016-August). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT.2016.7541663

Optimal differential privacy mechanisms under Hamming distortion for structured source classes. / Kalantari, Kousha; Sankar, Lalitha; Sarwate, Anand D.

Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory. Institute of Electrical and Electronics Engineers Inc., 2016. p. 2069-2073 7541663 (IEEE International Symposium on Information Theory - Proceedings; Vol. 2016-August).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kalantari, K, Sankar, L & Sarwate, AD 2016, Optimal differential privacy mechanisms under Hamming distortion for structured source classes. in Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory., 7541663, IEEE International Symposium on Information Theory - Proceedings, vol. 2016-August, Institute of Electrical and Electronics Engineers Inc., pp. 2069-2073, 2016 IEEE International Symposium on Information Theory, ISIT 2016, Barcelona, Spain, 7/10/16. https://doi.org/10.1109/ISIT.2016.7541663

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

Kalantari, Kousha ; Sankar, Lalitha ; Sarwate, Anand D. / Optimal differential privacy mechanisms under Hamming distortion for structured source classes. Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 2069-2073 (IEEE International Symposium on Information Theory - Proceedings).

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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.",

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Optimal differential privacy mechanisms under Hamming distortion for structured source classes

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Keywords

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