Hypothesis testing under maximal leakage privacy constraints

Jiachun Liao, Lalitha Sankar, Flavio P. Calmon, Vincent Y.F. Tan

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

14 Citations (Scopus)

Abstract

The problem of publishing privacy-guaranteed data for hypothesis testing is studied using the maximal leakage (ML) as a metric for privacy and the type-II error exponent as the utility metric. The optimal mechanism (random mapping) that maximizes utility for a bounded leakage guarantee is determined for the entire leakage range for binary datasets. For non-binary datasets, approximations in the high privacy and high utility regimes are developed. The results show that, for any desired leakage level, maximizing utility forces the ML privacy mechanism to reveal partial to complete knowledge about a subset of the source alphabet. The results developed on maximizing a convex function over a polytope may also of an independent interest.

Original languageEnglish (US)
Title of host publication2017 IEEE International Symposium on Information Theory, ISIT 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages779-783
Number of pages5
ISBN (Electronic)9781509040964
DOIs
StatePublished - Aug 9 2017
Event2017 IEEE International Symposium on Information Theory, ISIT 2017 - Aachen, Germany
Duration: Jun 25 2017Jun 30 2017

Other

Other2017 IEEE International Symposium on Information Theory, ISIT 2017
CountryGermany
CityAachen
Period6/25/176/30/17

Fingerprint

Data privacy
Hypothesis Testing
Leakage
Privacy
Testing
Random Mapping
Error Exponent
Type II error
Metric
Polytope
Convex function
Maximise
Entire
Binary
Partial
Subset
Approximation
Range of data

ASJC Scopus subject areas

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

Cite this

Liao, J., Sankar, L., Calmon, F. P., & Tan, V. Y. F. (2017). Hypothesis testing under maximal leakage privacy constraints. In 2017 IEEE International Symposium on Information Theory, ISIT 2017 (pp. 779-783). [8006634] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT.2017.8006634

Hypothesis testing under maximal leakage privacy constraints. / Liao, Jiachun; Sankar, Lalitha; Calmon, Flavio P.; Tan, Vincent Y.F.

2017 IEEE International Symposium on Information Theory, ISIT 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 779-783 8006634.

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

Liao, J, Sankar, L, Calmon, FP & Tan, VYF 2017, Hypothesis testing under maximal leakage privacy constraints. in 2017 IEEE International Symposium on Information Theory, ISIT 2017., 8006634, Institute of Electrical and Electronics Engineers Inc., pp. 779-783, 2017 IEEE International Symposium on Information Theory, ISIT 2017, Aachen, Germany, 6/25/17. https://doi.org/10.1109/ISIT.2017.8006634
Liao J, Sankar L, Calmon FP, Tan VYF. Hypothesis testing under maximal leakage privacy constraints. In 2017 IEEE International Symposium on Information Theory, ISIT 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 779-783. 8006634 https://doi.org/10.1109/ISIT.2017.8006634
Liao, Jiachun ; Sankar, Lalitha ; Calmon, Flavio P. ; Tan, Vincent Y.F. / Hypothesis testing under maximal leakage privacy constraints. 2017 IEEE International Symposium on Information Theory, ISIT 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 779-783
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