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A survey on differential privacy and applications

Xiong,P, Zhu,T-Q and Wang,X-F 2014, A survey on differential privacy and applications, Jisuanji Xuebao/Chinese Journal of Computers, vol. 37, no. 1, pp. 101-122, doi: 10.3724/SP.J.1016.2014.00101.

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Title A survey on differential privacy and applications
Author(s) Xiong,P
Zhu,T-QORCID iD for Zhu,T-Q orcid.org/0000-0003-3411-7947
Wang,X-F
Journal name Jisuanji Xuebao/Chinese Journal of Computers
Volume number 37
Issue number 1
Start page 101
End page 122
Total pages 22
Publisher Kexue Chubanshe / Science Press
Place of publication Beijing, China
Publication date 2014-01
ISSN 0254-4164
Keyword(s) Data mining
Data release
Differential privacy
Machine learning
Privacy preserving
Statistical query
Summary Privacy preserving in data release and mining is a hot topic in the information security field currently. As a new privacy notion, differential privacy (DP) has grown in popularity recently due to its rigid and provable privacy guarantee. After analyzing the advantage of differential privacy model relative to the traditional ones, this paper surveys the theory of differential privacy and its application on two aspects, privacy preserving data release (PPDR) and privacy preserving data mining (PPDM). In PPDR, we introduce the DP-based data release methodologies in interactive/non-interactive settings and compare them in terms of accuracy and sample complexity. In PPDM, we mainly summarize the implementation of DP in various data mining algorithms with interface-based/fully access-based modes as well as evaluating the performance of the algorithms. We finally review other applications of DP in various fields and discuss the future research directions.
Language chi
DOI 10.3724/SP.J.1016.2014.00101
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2014, Kexue Chubanshe / Science Press
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30072503

Document type: Journal Article
Collections: School of Information Technology
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.