CFP last date
20 March 2024
Reseach Article

Presenting a Hiding Algorithm for Improving Privacy Preserving in Association Rule Mining

by Somayeh Ghiasi, Mahdi Bateni
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 103 - Number 10
Year of Publication: 2014
Authors: Somayeh Ghiasi, Mahdi Bateni
10.5120/18111-9240

Somayeh Ghiasi, Mahdi Bateni . Presenting a Hiding Algorithm for Improving Privacy Preserving in Association Rule Mining. International Journal of Computer Applications. 103, 10 ( October 2014), 31-40. DOI=10.5120/18111-9240

@article{ 10.5120/18111-9240,
author = { Somayeh Ghiasi, Mahdi Bateni },
title = { Presenting a Hiding Algorithm for Improving Privacy Preserving in Association Rule Mining },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 103 },
number = { 10 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 31-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume103/number10/18111-9240/ },
doi = { 10.5120/18111-9240 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:34:12.328780+05:30
%A Somayeh Ghiasi
%A Mahdi Bateni
%T Presenting a Hiding Algorithm for Improving Privacy Preserving in Association Rule Mining
%J International Journal of Computer Applications
%@ 0975-8887
%V 103
%N 10
%P 31-40
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Association rules mining is one of data mining techniques to extract useful patterns in the framework of the law. The major problem of this technique on a database of sensitive information is disclosed to the security and privacy risks. One of the most effective solutions for maintaining privacy in data mining techniques to hide a lot of elements sensitive ( sensitive frequent patterns) reserved. In this study, an algorithm to hide the sensitive rules based on the rules and techniques to support the reduction of turbulence is presented. The proposed algorithm is to select the most appropriate transaction for changes, consider the degree of overlap between their response elements. Critical element in choosing transactions to correct the Frequency sensitive elements in the sensitive patterns and frequency patterns insensitive response elements in the balance. The proposed algorithm with algorithms ADSRRC, SIF-IDF and SL-HS dense and non-dense on four databases are implemented. Since the implementation of the proposed method compared with other algorithms reduced. Also, the number of missing rules changes the rules of the bogus transactions and the proposed algorithm is more efficient than other algorithms.

References
  1. F. Rajola, "Customer Relationship Management in the Financial Industry", Springer-Verlag Berlin Heidelberg, 2013.
  2. K. N. V. D. Sarath and V. Ravi, "Association rule mining using binary particle swarm¬¬optimization", Engineering ApplicationsofArtificial Intelligence, Vol. 26, 2013, pp. 1832–1840.
  3. D. Aruna Kumari, K. Rajasekhara Rao, and M. Suman. "Privacy Preserving Data Mining", Springer International Publishing, Vol. 249, 2014, pp. 517–524.
  4. V Garg, A. Singh, and D. Singh. "A Survey of Association Rule Hiding¬ lgorithms", IEEE 2014 Fourth International Conference on Communication Systems and Network Technologies, Vol. 24,2014,pp. 2676 – 2678.
  5. T. P Hong, C. W Lin, K. T Yang, and S. Wang. "Using TF-IDF to hide sensitive itemsets. ", Springer Science+Business Media Appl Intell DOI 10. 1007/s10489-012-0377-5,2012
  6. C-M. Wu and Y-F. Huang, "Privacy Preserving Association Rules by Using Branch-and-Bound Algorithm", Advances in Computer Science and Engineering, Vol. 141, 2012, pp. 409–416.
  7. V. Patidar, V. Shrivastava, and V. Shivastava. "A Generalized Association Rule Method for Privacy Preserving in Data Mininig", International Journal of Advanced Research in Computer Science and Software Engineering,Vol. 3,2013,pp. 703-706.
  8. X. Qi and M. Zong. "An Overview of Privacy Preserving Data Mining", Procedia Environmental Sciences, Vol. 12, 2012,pp. 1341-1347.
  9. Verykios V. S. , Bertino E. , Fovino I. N. , Provenza L. P. , Saygin, Y. , and Theodoridis "State-of-the-art in privacy preserving data mining", SIGMOD Record, Vol. 33, 2004, pp. 50-57.
  10. H. jiawei, K. Micheline. "Data Mining Canceps and Technique". second edition. Elsevier Computers in Industry, Vol. 64, 2013, pp. 776–784.
  11. R. Agrawal , T. Imielinski , and Sawmi. "A Mining association rules between sets of items in large databases. " ACM SIGMOD international conference on management of data, Vol. 14,1993, pp 207–216.
  12. S. Kotsiantis and D. Kanellopoulos, "Association Rules Mining: A Recent Overview", GESTS International Transactions on Computer Science and Engineering, Vol. 32 (1),2006, pp. 71-82.
  13. K. Shah, A. Thakkarand, and A. Ganatra. "Association Rule Hiding by Heuristic Approach to Reduce Side Effects & Hide Multiple R. H. S. Items", International Journal of Computer Applications (0975 – 8887) Vol45, 2012.
  14. Elisa Bertino, Dan Lin, and Wei Jiang, "A Survey of Quantification of Privacy Preserving Data Mining Algorithms", Springer, Vol. 169, 2008, Pages: 183–205.
  15. A. Divanis, Vassilios S. Verykios "Association Rule Hiding For Data Mining" Springer, DOI 10. 1007/978-1-4419-6569-1, Springer Science + Business Media, LLC 2010.
  16. M. Atallah, E. Bertino, A. Elmagarmid, M. Ibrahim, and V. S. Verykios. "Disclosure limitation of sensitive rules", Knowledge and Data Engineering Exchange, Vol. 16, 1999, pages45–52.
  17. T. -P. Hong and K. -T. Yang. "Several heuristic approaches to privvacy preserving data mining. " department of computer science and information enginieering national university of koashsiung. 2010
  18. H. Q. Le, S. Arch-int, H. X. Nguyen, and N. Arch-int, "Association rule hiding in risk management for retail supply chain collaboration", Computers in Industry, Vol. 64,2013, pp. 776–784.
  19. S. Verykios, "Association rule hiding methods", Wiley Online Library Interdisciplinary Reviews: Data Mining and Knowledge Discovery, Vol. 3, 2013, pp. 28–36.
  20. E. Dasseni, V. S. Verykios, A. K. Elmagarmid, and E. Bertino. "Hiding association rules by using confidence and support". In Proceedings of the 4th International Workshop on Information Hiding, Vol. 2137,2001, pp. 369–383.
  21. Y. Saygin, V. S. Verykios, and C. W. Clifton. "Using unknowns to prevent discovery of association rules. " ACM SIGMOD Record, Vol, 30, 2001, pp: 45–54.
  22. S. R. M. Oliveira and O. R. Zaïane. "An Efficient One-Scan Sanitization For Improving The Balance Between Privacy And Knowledge Discovery", Department of Computing Science University of Alberta, 2003.
  23. S. R. M. Oliveira and O. R. Zaïane. "Privacy preserving frequent itemset mining". In Proceedings of the IEEE International Conference on Privacy, Vol. 14,2005, pp. 43–54.
  24. S-L. Wang, B. Parikh, and A. Jafari. "Hiding informative association rule sets", Expert Systems with Applications, Vol. 33, 2007, pp. 316–323.
  25. C. N. Modi, U. P. Rao,,and D. R. Patel, "Maintaining privacy and data quality in privacy preserving association rule mining", Computing Communication and Networking Technologies (ICCCNT) International Conference on,2010 , pp 1-6.
  26. D. Jain, P. Khatri, R. Soni, and B. Kumar Chaurasia, "Hiding Sensitive Association Rules without Alteringthe Support of Sensitive Item(s)", Institute for Computer Sciences, Social Informatics and Telecommunications Engineering,Vol. 84,2012,pp. 500-509.
  27. K. Shah, A. Thakkarand, and A. Ganatra. "Association Rule Hiding by Heuristic Approach to Reduce Side Effects & Hide Multiple R. H. S. Items", International Journal of Computer Applications Vol45, 2012,pp: (0975 – 8887).
  28. G. Salton, Fox EA, and H. Wu , "Extended boolean information retrieval Commun",ACM Vol. 26, 1983,pp:1022–1036.
Index Terms

Computer Science
Information Sciences

Keywords

privacy hiding the sensitive rules Data Mining secure database.