Survey on Association Rule Hiding Techniques

Authors

  • G. Bhavani  Department of Computer Science and Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India
  • Dr. S. Sivakumari  Department of Computer Science and Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India

DOI:

https://doi.org//10.32628/IJSRSET196368

Keywords:

Association Rule Hiding, Data Mining, Privacy Preserving Data Mining, Sensitive data.

Abstract

Data mining process extracts useful information from a large amount of data. The most interesting part of data mining is discovering the unseen patterns without unpacking sensitive knowledge. Privacy Preserving Data Mining abbreviated as PPDM deals with the issue of sustaining the privacy of information. This methodology covers the sensitive information from disclosure. PPDM techniques are established for hiding the sensitive information even after performing the data mining. One of the practices to hide the sensitive association rules is termed as association rule hiding. The main objective of association rule hiding algorithm is to slightly adjust the original database so that no sensitive association rule is derived from it. The following article presents a detailed survey of various association rule hiding techniques for preserving privacy in data mining. At first, different techniques developed by previous researchers are studied in detail. Then, a comparative analysis is carried out to know the limitations of each technique and then providing a suggestion for future improvement in association rule hiding for privacy preservation.

References

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Published

2019-06-30

Issue

Section

Research Articles

How to Cite

[1]
G. Bhavani, Dr. S. Sivakumari, " Survey on Association Rule Hiding Techniques, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 6, Issue 3, pp.300-305, May-June-2019. Available at doi : https://doi.org/10.32628/IJSRSET196368