A Statistical Decision-Theoretic Approach for Measuring Privacy Risk and Utility in Databases

Alisa Miyashita, Akira Kamatsuka, Takahiro Yoshida, Toshiyasu Matsushima

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

Abstract

In this paper, we deal with the problem of database statistics publishing with privacy and utility guarantees. While various privacy and utility metrics have been proposed, purposes of using the statistics for a user and an adversary and their background knowledge about the database have not been specified. We model the user and the adversary from two perspectives. First, we model their background knowledge: knowledge of statistics of the database and knowledge of distribution for the database. Then we model the purposes of them as decision functions in statistical decision theory. Privacy and utility metrics are defined based on risk functions. Comparison of the statistical decision-theoretic framework we propose and differential privacy framework is made through a numerical example.

Original languageEnglish
Title of host publication2020 54th Annual Conference on Information Sciences and Systems, CISS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728140841
DOIs
Publication statusPublished - 2020 Mar
Event54th Annual Conference on Information Sciences and Systems, CISS 2020 - Princeton, United States
Duration: 2020 Mar 182020 Mar 20

Publication series

Name2020 54th Annual Conference on Information Sciences and Systems, CISS 2020

Conference

Conference54th Annual Conference on Information Sciences and Systems, CISS 2020
CountryUnited States
CityPrinceton
Period20/3/1820/3/20

Keywords

  • Differential Privacy
  • Privacy
  • Statistical Decision Theory
  • Utility

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'A Statistical Decision-Theoretic Approach for Measuring Privacy Risk and Utility in Databases'. Together they form a unique fingerprint.

  • Cite this

    Miyashita, A., Kamatsuka, A., Yoshida, T., & Matsushima, T. (2020). A Statistical Decision-Theoretic Approach for Measuring Privacy Risk and Utility in Databases. In 2020 54th Annual Conference on Information Sciences and Systems, CISS 2020 [9086260] (2020 54th Annual Conference on Information Sciences and Systems, CISS 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CISS48834.2020.1570617434