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ARM-Based Privacy Preserving for Medical Data Publishing

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Cloud Computing and Security (ICCCS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9483))

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Abstract

The increasing use of electronic medical records (EMR) makes the medical data mining becomes a hot topic. Consequently, medical privacy invasion attracts people’s attention. Among these, we are particularly interested in the privacy preserving for association rule mining (ARM). In this paper, we improve the traditional reconstruction-based privacy preserving data mining (PPDM) and propose a new architecture for medical data publishing with privacy preserving, and we present a sanitization algorithm for the sensitive rules hiding. In this architecture, the sensitive rules are strictly controlled as well as the side effects are minimized. And finally we performed an experiment to evaluate the proposed architecture.

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Author information

Authors and Affiliations

  1. School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China

    Zhang Fengli & Bai Yijing

Authors
  1. Zhang Fengli
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  2. Bai Yijing
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Editor information

Editors and Affiliations

  1. Nanjing University of Aeronautics and As, Nanjing, China

    Zhiqiu Huang

  2. Nanjing University of Information Scienc, Nanjing, China

    Xingming Sun

  3. Nanjing, China

    Junzhou Luo

  4. Nanjing University of Aeronautics and As, Nanjing, China

    Jian Wang

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Fengli, Z., Yijing, B. (2015). ARM-Based Privacy Preserving for Medical Data Publishing. In: Huang, Z., Sun, X., Luo, J., Wang, J. (eds) Cloud Computing and Security. ICCCS 2015. Lecture Notes in Computer Science(), vol 9483. Springer, Cham. https://doi.org/10.1007/978-3-319-27051-7_6

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  • DOI: https://doi.org/10.1007/978-3-319-27051-7_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27050-0

  • Online ISBN: 978-3-319-27051-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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