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Utilization of Imprecise Rules for Privacy Protection

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Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11471))

Abstract

In this paper, we utilize imprecise rules for privacy protection in the publication of data sets. We assume that data sets show the classification results with more than two classes. First k-anonymous imprecise rules are induced. Using several k-anonymous imprecise rules explaining an object, the object is replaced with several imprecise patterns corresponding to the k-anonymous imprecise rules which are common in at least k objects. In this way, privacy protected data tables are composed. The proposed data table is investigated by numerical experiments from its usefulness in rule induction as well as from its privacy protection ability. The results show that the proposed method will be satisfactorily useful.

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Acknowledgment

This work was partially supported by JSPS KAKENHI Grant Number 18H01658.

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Authors and Affiliations

  1. Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka, 560-8531, Japan

    Masahiro Inuiguchi & Keisuke Washimi

Authors
  1. Masahiro Inuiguchi
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  2. Keisuke Washimi
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Corresponding author

Correspondence to Masahiro Inuiguchi .

Editor information

Editors and Affiliations

  1. Osaka University, Toyonaka, Osaka, Japan

    Hirosato Seki

  2. Institute for Chemical Research, Kyoto University, Uji, Kyoto, Japan

    Canh Hao Nguyen

  3. Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan

    Van-Nam Huynh

  4. Osaka University, Toyonaka, Osaka, Japan

    Masahiro Inuiguchi

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Inuiguchi, M., Washimi, K. (2019). Utilization of Imprecise Rules for Privacy Protection. In: Seki, H., Nguyen, C., Huynh, VN., Inuiguchi, M. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2019. Lecture Notes in Computer Science(), vol 11471. Springer, Cham. https://doi.org/10.1007/978-3-030-14815-7_22

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  • DOI: https://doi.org/10.1007/978-3-030-14815-7_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-14814-0

  • Online ISBN: 978-3-030-14815-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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