CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

A Survey on Association Rule Hiding Methods

by Khyati B. Jadav, Jignesh Vania, Dhiren R. Patel
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 82 - Number 13
Year of Publication: 2013
Authors: Khyati B. Jadav, Jignesh Vania, Dhiren R. Patel
10.5120/14177-2357

Khyati B. Jadav, Jignesh Vania, Dhiren R. Patel . A Survey on Association Rule Hiding Methods. International Journal of Computer Applications. 82, 13 ( November 2013), 20-25. DOI=10.5120/14177-2357

@article{ 10.5120/14177-2357,
author = { Khyati B. Jadav, Jignesh Vania, Dhiren R. Patel },
title = { A Survey on Association Rule Hiding Methods },
journal = { International Journal of Computer Applications },
issue_date = { November 2013 },
volume = { 82 },
number = { 13 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = { 20-25 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume82/number13/14177-2357/ },
doi = { 10.5120/14177-2357 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:58:12.481145+05:30
%A Khyati B. Jadav
%A Jignesh Vania
%A Dhiren R. Patel
%T A Survey on Association Rule Hiding Methods
%J International Journal of Computer Applications
%@ 0975-8887
%V 82
%N 13
%P 20-25
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In recent years, the use of data mining techniques and related applications has increased a lot as it is used to extract important knowledge from large amount of data. This has increased the disclosure risks to sensitive information when the data is released to outside parties. Database containing sensitive knowledge must be protected against unauthorized access. Seeing this it has become necessary to hide sensitive knowledge in database. To address this problem, Privacy Preservation Data Mining (PPDM) include association rule hiding method to protect privacy of sensitive data against association rule mining. In this paper, we survey existing approaches to association rule hiding, along with some open challenges. We have also summarized few of the recent evolution.

References
  1. M. Atallah, E. Bertino, A. Elmagamind, M. Ibrahim, and V. S. Verykios "Disclosure limitation of sensitive rules," . In Proc. of the 1999 IEEE Knowledge and Data Engineering Exchange Workshop(KDEX 1999), pp. 45-52.
  2. R. Agrawal, T. Imielinski, and A. Swami, "Mining association rules between sets of items in large databases". In Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, Washington, DC, May 26-28 1993, pp. 207-216.
  3. S. Vijayarani, A. Tamilarasi and R. SeethaLakshmi, "Privacy Preserving Data Mining Based on Association Rule-A Survey". In Proc. of the International Conference on Communication and Computational Intelligence-2010, pp. 99-103.
  4. K. Shah, A. Thakkar and A. Ganatra, "A Study on Association Rule Hiding Approaches". (IJEAT)International Journal of Engineering and Advanced Technology, vol 3, issue-3, February 2012, pp. 72-76.
  5. V. S. Verykios, A. Elmagarmid, E. Bertino, Y. Saygin, and E. Dasseni, "Association rule hiding," IEEE Transactions on Knowledge and Data Engineering, Vol. 16, No. 4, 434–447, 2004.
  6. S. Oliveira, O. Zaïane, and Y. Sayg?n, "Secure Association Rule Sharing," In: Dai, H. , Srikant, R. , Zhang, C. (eds. ) PAKDD 2004. LNCS (LNAI), Vol. 3056, pp. 74–85. Springer, Heidelberg, 2004.
  7. Y. H. Wu, C. M. Chiang and A. L. P. Chen, "Hiding Sensitive Association Rules with Limited Side Effects", IEEE Transactions on Knowledge and Data Engineering, Vol. 19, No. 1, Jan. 2007, pp. 29-42.
  8. Y. Saygin, V. Verykios, and C. Clifton, "Using Unknowns to Prevent Discovery of Association Rules" ACM SIGMOD, Vol. 30, No. 4, pp. 45–54, 2001.
  9. Y. Saygin, V. Verykios, and A. Elmagarmid, "Privacy preserving association rule mining," In: Proc. Int'l. Workshop on Research Issues in Data Engineering (RIDE 2002), pp. 151–163, 2002.
  10. S. Wang, and A. Jafari, "Using unknowns for hiding sensitive predictive association rules," In: Proc. IEEE Int'l. Conf. Information Reuse and Integration (IRI 2005), pp. 223–228, 2005.
  11. X. Sun, and P. Yu, "A Border-Based Approach for Hiding Sensitive Frequent Itemsets," In: Proc. Fifth IEEE Int'l. Conf. Data Mining (ICDM 2005), pp. 426–433, 2005.
  12. A. Gkoulalas-Divanis, V. Verykios, "An Integer Programming Approach for Frequent Itemset Hiding," In: Proc. ACM Conf. Information and Knowledge Management (CIKM 2006), pp. 748–757 2006.
  13. T. Mielikainen, "On inverse frequent set mining", In Proc. of 3rd IEEE ICDM Workshop on Privacy Preserving Data Mining. IEEE Computer Society, 2003, pp. 18-23.
  14. Y. Guo, "Reconstruction-Based Association Rule Hiding" In Proc. of SIGMOD2007 Ph. D. Workshop on Innovative Database Research 2007(IDAR2007), June 2007, pp. 51-56.
  15. J. Vaidya, and C. Clifton, "Privacy preserving association rule mining in vertically partitioned data," In proc. Int'l Conf. Knowledge Discovery and Data Mining, pp. 639–644, July 2002.
  16. M. Kantarcioglu, and C. Clifton, "Privacy-preserving distributed mining of association rules on horizontally partitioned data," IEEE Transactions on Knowledge and Data Engineering, Vol. 16, No. 9, pp. 1026-1037, Sept. 2004.
  17. C. N. Modi, U. P. Rao, and D. R. Patel, "Maintaining privacy and data quality in privacy preserving association rule mining," 2010 Second International conference on Computing, Communication and Networking Technologies, pp. 1–6, Jul. 2010.
  18. N Domadiya and U. P. Rao, "Hiding Sensitive Association Rules to Maintain Privacy and Data Quality in Database" 2013 3rd IEEE International Advance Computing Conference (IACC), pp. 1306-1310, 2013.
  19. K. Pathak, N. S. Chaudgari and A. Tiwari, "Privacy Preserving Association Rule Mining by Introducing Concept of Impact Factor" 2012 7th IEEE Conference on Industrial Electronics and Application(ICIEA), pp. 1458-1461, 2012.
  20. S-L Wang, T Hong, Y-C Tsai, and H-Y Kao, "Hiding Sensitive Association Rules on Stars" 2010 IEEE International Conference on Granular Computing, pp 505-508, 2010.
  21. H. Q. Le, "Association rule hiding in risk management for retail supply chain collaboration" 2013 Elsevier on Computers in Industry 64, pp. 776-784, 2013.
  22. V. S. Verkios, "Association rule hiding methods" 2013 John Wiley & Sons, Inc, Vol. 3, January/February 2013, pp. 28-38.
  23. C. Modi, U. P. Rao and D. R. Patel, "A Survey on Preserving Privacy for Sensitive Association Rules in Databases" Springer-Verlag Berlin Heidelberg 2010, pp. 538-544.
  24. A. Gkoulalas-Divanis, and V. S. Verykios, " Exact knowledge hiding through database extension" IEEE Trans Knowledge Data Eng 2009, pp. 699–713.
  25. G. Tuncel, and G. Alpan, "Risk assessment and management for supply chain networks": a case study, Computers in Industry 61 (2010), pp. 250–259, 2010.
  26. J. Han, and M. Kamber, Data Mining: Concepts and Techniques, pp. 227–245. Morgan Kaufmann Publishers, San Francisco, 2001.
  27. K. Duraiswamy, and D. Manjula, "Advanced approach in sensitive rule hiding," Modern Ap-plied Science," Vol. 3, No. 2, 2009.
  28. G. V. Moustakides, and V. S. Verykios, "A Max-Min Approach for Hiding Frequent Itemsets," In: Proc. Sixth IEEE Int'l. Conf. Data Mining (ICDM 2006), pp. 502–506.
Index Terms

Computer Science
Information Sciences

Keywords

Data mining Privacy preserving data mining

Powered by PhDFocusTM