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A Hybrid Algorithm for Association Rule Hiding using Representative Rule

by Vikram Garg, Anju Singh, Divakar Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 97 - Number 9
Year of Publication: 2014
Authors: Vikram Garg, Anju Singh, Divakar Singh
10.5120/17033-7334

Vikram Garg, Anju Singh, Divakar Singh . A Hybrid Algorithm for Association Rule Hiding using Representative Rule. International Journal of Computer Applications. 97, 9 ( July 2014), 9-14. DOI=10.5120/17033-7334

@article{ 10.5120/17033-7334,
author = { Vikram Garg, Anju Singh, Divakar Singh },
title = { A Hybrid Algorithm for Association Rule Hiding using Representative Rule },
journal = { International Journal of Computer Applications },
issue_date = { July 2014 },
volume = { 97 },
number = { 9 },
month = { July },
year = { 2014 },
issn = { 0975-8887 },
pages = { 9-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume97/number9/17033-7334/ },
doi = { 10.5120/17033-7334 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:23:38.190229+05:30
%A Vikram Garg
%A Anju Singh
%A Divakar Singh
%T A Hybrid Algorithm for Association Rule Hiding using Representative Rule
%J International Journal of Computer Applications
%@ 0975-8887
%V 97
%N 9
%P 9-14
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In the recent years, data mining has emerged as a very popular tool for extracting hidden knowledge from collection of large amount of data. One of the major challenges of data mining is to find the hidden knowledge in the data while the sensitive information is not revealed. Many strategies have been proposed to hide the information containing sensitive data. Privacy preserving data mining is an answer to such challenge. Association rule hiding is one of the PPDM techniques to protect the sensitive association rule generated by Association rule mining (ARM). In this paper, the data distortion technique for hiding the sensitive information is used. The proposed approach uses the concept of Representative Rule (RR) which is used to prune the number of association rule. The proposed algorithm hides the more number of rules while making the fewer database scans.

References
  1. Agrawal R. & Srikant R. , "Privacy preserving data mining" , In ACM SIGMOD conference on management of data, pp. 439-450, 2000.
  3. Clifton C. , "Protecting against data mining through samples" In Proceedings of the thirteenth annual IFIP WG 11. 3 working conference on database security, pp. 193-207, 1999.
  5. Clifton C. , "Using sample size to limit exposure to data mining", Journal of Computer Security, Vol. 8, pp. 281-307, 2000.
  7. Dasseni E. , Verykios V. , Elmagarmid A. & Bertino E. , "Hiding association rules by using confidence and support" In Proceedings of 4th information hiding workshop, pp. 369-383,2001.
  9. Dhutraj Niteen ,Sasane Siddhart,Kshirsagar Vivek, "Hiding Sensitive Association Rule for Privacy Preservation", IEEE Transactions on Knowledge And Data Engineering, 2013.
  11. Gulwani Padam,"Association Rule Hiding by Positions Swapping of Support and Confidence", International journal of Information Technology and Computer Science, Vol. 4, pp. 54-61, 2012.
  13. Jadav Khyati B. ,Vania Jignesh,Patel Dhiren R. , "A Survey on Association Rule Hiding Methods", International Journal of Computer Applications, Vol. 82, pp. 20-25, 2013.
  15. Kryszkiewicz, M. , "Representative Association Rules and Minimum Condition Maximum Consequence Association Rules", PKDD, Vol. 1510, pp. 361-369, Springer, 1998.
  17. Modi C. N. , Rao U. P. & Patel D. R. , "Maintaining privacy and data quality in privacy preserving association rule mining", International Conference on Computing Communication and Networking Technologies (ICCCNT),pp. 1-6, 2010.
  19. Oliveira S. & Zaiane O. , "Algorithms for balancing privacy and knowledge discovery in association rule mining" , In Proceedings of 7th international database engineering and applications symposium (IDEAS03), pp. 54-63, 2003.
  21. Oliveira Stanley R. M. ,Osmar R. Zaiane, "Privacy Preserving Frequent Itemset Mining", IEEE International Conference on Data Mining Workshop on Privacy, Security, and Data Mining,Vol. 14, pp. 19-26, 2002.
  23. Shah Komal ,Thakkar Amit ,Ganatra Amit," A Study on Association Rule Hiding Approaches", International Journal of Engineering and Advanced Technology (IJEAT), 2012.
  25. Wang Shyue-Liang,Maskey Rajeev,Jafari Ayat & Hong Tzung-Pei,"Efficient sanitization of informative association rules" ,ACM, Expert Systems with Applications: An International Journal, 2008.
  27. Wang Shyue-Liang,Parikh Bhavesh,Jafari Ayat, "Hiding informative association rule sets", ELSEVIER, Expert Systems with Applications, pp. 316-323, 2007.
  29. Wang Shyue-Liang,Patel Dipen,Jafari Ayat & Hong Tzung-Pei, "Hiding collaborative recommendation association rules" ,Springer Science+Business Media, LLC 2007.
  31. Weng Chih-Chia ,Chen Shan-Tai & Lo Hung-Che "A Novel Algorithm for Completely Hiding Sensitive Association Rules" ,IEEE Intelligent Systems Design and Applications, Vol. 2, pp. 202-208 2008.
Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Privacy Preserving Association Rule Hiding Representative Rule

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