Data-driven approach for evaluating risk of disclosure and utility in differentially private data release

Kang Cheng Chen, Chia Mu Yu, Bo Chen Tai, Szu Chuang Li, Yao Tung Tsou, Yennun Huang, Chia Ming Lin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Differential privacy (DP) is a popular technique for protecting individual privacy and at the same for releasing data for public use. However, very few research efforts are devoted to the balance between the corresponding risk of data disclosure (RoD) and data utility. In this paper, we propose data-driven approaches for differentially private data release to evaluate RoD, and offer algorithms to evaluate whether the differentially private synthetic dataset has sufficient privacy. In addition to the privacy, the utility of the synthetic dataset is an important metric for differentially private data release. Thus, we also propose the data-driven algorithm via curve fitting to measure and predict the error of the statistical result incurred by random noise added to the original dataset. Finally, we present an algorithm for choosing appropriate privacy budget E with the balance between the privacy and utility.

Original languageEnglish
Title of host publicationProceedings - 31st IEEE International Conference on Advanced Information Networking and Applications, AINA 2017
EditorsTomoya Enokido, Hui-Huang Hsu, Chi-Yi Lin, Makoto Takizawa, Leonard Barolli
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1130-1137
Number of pages8
ISBN (Electronic)9781509060283
DOIs
StatePublished - 5 May 2017
Event31st IEEE International Conference on Advanced Information Networking and Applications, AINA 2017 - Taipei, Taiwan
Duration: 27 Mar 201729 Mar 2017

Publication series

NameProceedings - International Conference on Advanced Information Networking and Applications, AINA
ISSN (Print)1550-445X

Conference

Conference31st IEEE International Conference on Advanced Information Networking and Applications, AINA 2017
CountryTaiwan
CityTaipei
Period27/03/1729/03/17

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