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Privacy Preserving Association Rule Mining Algorithm Based on Hybrid Partial Hiding Strategy

In: Liss 2013

Author

Listed:
  • Jianming Zhu

    (Central University of Finance and Economics)

  • Zhanyu Li

    (Central University of Finance and Economics)

Abstract

Privacy-preserving data mining (PPDM) is one of the newest trends in privacy and security research. It is driven by one of the major policy issues of the information ear – the right to privacy. In order to improve the privacy preservation of association rule mining, a hybrid partial hiding algorithm (HPH) is proposed. The original data set can be interference and transformed by different random parameters. Then, the algorithm of generating frequent items based on HPH is presented. Finally, it can be proved that the privacy of HPH algorithm is better than the original algorithm.

Suggested Citation

  • Jianming Zhu & Zhanyu Li, 2015. "Privacy Preserving Association Rule Mining Algorithm Based on Hybrid Partial Hiding Strategy," Springer Books, in: Runtong Zhang & Zhenji Zhang & Kecheng Liu & Juliang Zhang (ed.), Liss 2013, pages 1065-1070, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-40660-7_160
    DOI: 10.1007/978-3-642-40660-7_160
    as

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