Data mining is basically a process of identifying different patterns from huge amount of data. Association rule hiding technique target to find out dependency relationships transversely attributes. It may reveal sensitive information. With widespread applications of data mining techniques to diverse domains, privacy preservation becomes compulsory. Association rule hiding is one of the important techniques of privacy preserving data mining to keep the sensitive association rules generated by association rule mining. In this paper we talk about heuristic approach for hiding sensitive rules. The proposed technique provides us solution of privacy disclosure and hides the sensitive rules.

Association Rule Hiding, Data Mining, Privacy Preserving Data Mining, Distortion, Representative Rule.

[1] Masooda Modaka,Rizwana Shaikhb.” Privacy Preserving Distributed Association Rule Hiding Using Concept Hierarchy”, 7th International Conference on Communication, Computing and Virtualization 2016. Procedia Computer Science 79 (2016)993–1000.

[2] Putri, A walia W. Laksmiwati Hira.” Hybrid Transformation in Privacy-Preserving Data Mining” 978-1-5090-5671-2/16/$31.00 ©2016 IEEE.

[3] Mohamed Refaat Abdellah H. Aboelseoud ’
Khalid Shafee M. Badr Senousy “Privacy Preserving Association Rule Hiding Techniques: Current Research Challenges” International Journal of Computer Applications (0975 – 8887) Volume 136 – No.6, February 2016.

[4] Kasthuri S1 and Meyyappan T2 “Hiding Sensitive Association Rule Using Heuristic Approach”, International Journal of Data Mining & Knowledge Management Process (IJDKP) Vol.3, No.1, January 2013DOI.

[5] Umesh Kumar Sahu Anju Singh “Approaches for Privacy Preserving Data Mining by Various Associations Rule Hiding Algorithms – A Survey”, International Journal of Computer Applications (0975 – 8887) Volume 134 – No.11, January 2016.

[6] Khyati B. Jadav, Jignesh Vania Dhiren R. Patel, Ph.D “A Survey on Association Rule Hiding Methods”, International Journal of Computer Applications (0975 – 8887) Volume 82 – No 13, November 2013.

[7] K. Naga Prasanthi “A Review on Privacy Preserving Data Mining Techniques” International Journal of Advanced Research in Computer Science and Software Engineering Volume 6, Issue 3, March 2016.

[8] Vinita Shah Divya C. Kalariya Jay Vala “Association Rule Hiding based on Heuristic Approach by Deleting Item at R.H.S. Side of Sensitive Rule”, International Journal of Computer Applications (0975 – 8887) Volume 122 –No.8, July 2015.

[9]Ruchi.P.Kanekar1, Prof. Rachel Dhanaraj2 “Adding Dummy Items To Hide Sensitive Association Rules” IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661,p-ISSN: 2278-8727 PP 06-10”

[9] Xueyun Li Zheng Yan Peng Zhang “A Review on Privacy-Preserving Data Mining”, December 2014.

[10]Mrs. Geeta S. Navale Dr. Suresh N. Mali “A Survey on Sensitive Association Rules Hiding Methods”, 978-1-5386-4008-1/17/$31.00 ©2017 IEEE.

[11]Melissa Fernandes Joanne Gomes “Heuristic Approach for Association Rule Hiding using ECLAT”, 978-1-5090-4381-1/17/$31.00 © 2017 IEEE

[12] Apoorva Joshi,, Pratima Gautam “A survey on Sanitizing Methods in Association Rule Hiding Technique” International Journal Of Scientific Research in Computer science, Engineering and Information Technology” ,volume2 Issue 6 2017.

[13] Li Jingquan. "Privacy-Enhancing Data Mining: Issues, Techniques and Measures". University of Illinois, United State of America, 2004.

[14] Xingyu Geng BP., Zhang J. "Combined Data Distortion Strategies for Privacy-Preserving Data Mining". Southwest Petroleum University, China and University of Kentucky, United States of America. 2010.

[15] Jajodia., C.F.a.S., The inference problem: A survey, in SIGKDD Exploration Newsletter. 2002. p. 6-11.

[16] A. Parmar, U.P.R., D. R. Patel. “Blocking based approach for classification Rule hiding to Preserve the Privacy in Database”. In proceedings of International Symposium on Computer Science and Society, IEEE 2011.
[17] Animesh Tripathy, M.P. “A novel framework for preserving privacy of data using correlation analysis”. In Proceedings of the International Conference on Advances in Computing, Communications and Informatics (ICACCI `12). ACM. 2012. NY, USA.

[18] Gkoulalas-Divanis and V.S.Verykios, “An Integer Programming Approach for Frequent Itemset Hiding”, In Proc. ACM Conf. Information and Knowledge Management (CIKM’06), Nov. 2006
[19] Y. Li, M. Chen, Q. Li, and W. Zhang, “Enabling multilevel trust in privacy preserving data mining,” IEEE Transactions on Knowledge and Data Engineering, vol.24, pp.1598-1612, 2012.

[20] Gkoulalas-Divanis and V.S. Verykios, “Exact Knowledge Hiding through Database Extension,” IEEE Transactions on Knowledge and Data Engineering, vol. 21(5), May 2009, pp. 699-713.