IMPROVEMENT OF CUCKOO ALGORITHM FOR ASSOCIATION RULE HIDING PROBLEM

Authors

  • Đoàn Minh Khuê The Faculty of Information Technology, Dalat University, Viet Nam,
  • Lê Hoài Bắc The Faculty of Information Technology, University of Science, VNU Hochiminh City, Viet Nam,

DOI:

https://doi.org/10.37569/DalatUniversity.8.2.410(2018)

Keywords:

Cuckoo optimization algorithm, Privacy-preserving data mining, Sensitive association rule hiding, Side effect.

Abstract

Nowadays, the problem of data security in the process of data mining receives more attention. The question is how to balance between exploiting legal data and avoiding revealing sensitive information. There have been many approaches, and one remarkable approach is privacy preservation in association rule mining to hide sensitive rules. Recently, a meta-heuristic algorithm is relatively effective for this purpose, which is cuckoo optimization algorithm (COA4ARH). In this paper, an improved version of COA4ARH is presented for calculating the minimum number of sensitive items which should be removed to hide sensitive rules, as well as limit the loss of non-sensitive rules. The experimental results gained from three real datasets showed that the proposed method has better results compared to the original algorithm in several cases.

References

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Published

01-07-2018

Volume and Issues

Section

Natural Sciences and Technology

How to Cite

Khuê, Đoàn M., & Bắc, L. H. (2018). IMPROVEMENT OF CUCKOO ALGORITHM FOR ASSOCIATION RULE HIDING PROBLEM. Dalat University Journal of Science, 8(2), 45-58. https://doi.org/10.37569/DalatUniversity.8.2.410(2018)

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