Open Access   Article

Privacy Preservation for Association Rule Mining

N. S. Mrudula Jyothi1 , A. Suraj Kumar2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-12 , Page no. 7-11, Dec-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i12.711

Online published on Dec 31, 2018

Copyright © N. S. Mrudula Jyothi, A. Suraj Kumar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Citation

IEEE Style Citation: N. S. Mrudula Jyothi, A. Suraj Kumar, “Privacy Preservation for Association Rule Mining”, International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.7-11, 2018.

MLA Style Citation: N. S. Mrudula Jyothi, A. Suraj Kumar "Privacy Preservation for Association Rule Mining." International Journal of Computer Sciences and Engineering 6.12 (2018): 7-11.

APA Style Citation: N. S. Mrudula Jyothi, A. Suraj Kumar, (2018). Privacy Preservation for Association Rule Mining. International Journal of Computer Sciences and Engineering, 6(12), 7-11.

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Abstract

Data mining is the process of extracting hidden patterns of data. Association rule mining is an important data mining task that finds an interesting association among a large set of a data item. Association rule hiding is one of the techniques of privacy-preserving data mining to protect the association rules generated by association rule mining. In this paper, proposed a new data distortion technique for hiding sensitive association rules. Algorithms based on this technique either hide a specific rule using data alteration technique or hide the rules depending on the sensitivity of the items to be hidden. The proposed technique uses the idea of representative rules to prune the rules first and then hides the sensitive rules.

Key-Words / Index Term

Data mining, Association rule mining, Support , Confidence

References

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