A new approach to preserve privacy data mining based on fuzzy theory in numerical database

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

2 Citations (Scopus)

Abstract

With the rapid development of information techniques, data mining approaches have become one of the most important tools to discover the in-deep associations of tuples in large-scale database. Hence how to protect the private information is quite a huge challenge, especially during the data mining procedure. In this paper, a new method is proposed for privacy protection which is based on fuzzy theory. The traditional fuzzy approach in this area will apply fuzzification to the data without considering its readability. A new style of obscured data expression is introduced to provide more details of the subsets without reducing the readability. Also we adopt a balance approach between the privacy level and utility when to achieve the suitable subgroups. An experiment is provided to show that this approach is suitable for the classification without a lower accuracy. In the future, this approach can be adapted to the data stream as the low computation complexity of the fuzzy function with a suitable modification.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
Volume9069
DOIs
Publication statusPublished - 2014 Feb 24
Event5th International Conference on Graphic and Image Processing, ICGIP 2013 - Hong Kong, China
Duration: 2013 Oct 262013 Oct 27

Other

Other5th International Conference on Graphic and Image Processing, ICGIP 2013
CountryChina
CityHong Kong
Period13/10/2613/10/27

Fingerprint

privacy
data mining
Fuzzy Theory
Privacy
Data mining
Data Mining
Privacy Protection
Fuzzy Function
Private Information
subgroups
Data Streams
set theory
Subgroup
Subset
Experiment
Experiments
Style

Keywords

  • anonymity
  • data mining
  • database utility
  • fuzzy theory
  • Privacy protection

ASJC Scopus subject areas

  • Applied Mathematics
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics

Cite this

Cui, R., & Kim, H. J. (2014). A new approach to preserve privacy data mining based on fuzzy theory in numerical database. In Proceedings of SPIE - The International Society for Optical Engineering (Vol. 9069). [90691A] https://doi.org/10.1117/12.2051002

A new approach to preserve privacy data mining based on fuzzy theory in numerical database. / Cui, Run; Kim, Hyong Joong.

Proceedings of SPIE - The International Society for Optical Engineering. Vol. 9069 2014. 90691A.

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

Cui, R & Kim, HJ 2014, A new approach to preserve privacy data mining based on fuzzy theory in numerical database. in Proceedings of SPIE - The International Society for Optical Engineering. vol. 9069, 90691A, 5th International Conference on Graphic and Image Processing, ICGIP 2013, Hong Kong, China, 13/10/26. https://doi.org/10.1117/12.2051002
Cui R, Kim HJ. A new approach to preserve privacy data mining based on fuzzy theory in numerical database. In Proceedings of SPIE - The International Society for Optical Engineering. Vol. 9069. 2014. 90691A https://doi.org/10.1117/12.2051002
Cui, Run ; Kim, Hyong Joong. / A new approach to preserve privacy data mining based on fuzzy theory in numerical database. Proceedings of SPIE - The International Society for Optical Engineering. Vol. 9069 2014.
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