Sri Vasavi College, Erode Self-Finance Wing 3rd February 2017 National Conference on Computer and Communication NCCC’17

Format: Volume 5, Issue 1, No 12, 2017

Copyright: All Rights Reserved ©2017

Year of Publication: 2017

Author: B.Kowsalya,N.Kokila


View PDF Format


This research paper contains an overview of the new and rapidly emerging research area of privacy preserving data mining. Privacy preserving in data mining has been a heart favorite topic of researchers from many years. Every organization contains sensitive data & such data is needed to be protected from the unauthorized access. This paper contains the comprehensive survey of traditional and modern privacy preserving data mining methods. Advantages and disadvantages of the existing algorithms are discussed a classification hierarchy that sets the basis for analyzing the work which has been performed in this context.


[1] Aris Gkoulalas–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 [2] M. Atallah, E. Bertino, A. Elmagarmid, M. Ibrahim, and V. S. Verykios ―Disclosure limitation of sensitive rules, ‖.In Proc. of the 1999 IEEE Knowledge and Data Engineering Exchange Workshop (KDEX’99), pp. 45–52, 1999. [3] Vassilios S. Verykios, A.K. Elmagarmid, E. Bertino, Y. Saygin, and E. Dasseni, ―Association Rule Hiding,‖ IEEE Transactions on Knowledge and Data Engineering, vol. 16, no. 4, pp. 434-447, 2004. [4] Shyue-Liang Wang; Bhavesh Parikh,; Ayat Jafari, ―Hiding informative association rule sets‖, ELSEVIER, Expert Systems with Applications 33 (2007) 316–323,2006 [5] Shyue-LiangWang ;Dipen Patel ;Ayat Jafari ;Tzung-Pei Hong, ―Hiding collaborative recommendation association rules‖, Published online: 30 January 2007, Springer Science+Business Media, LLC 2007 [6] Shyue-Liang Wang; Rajeev Maskey; Ayat Jafari; Tzung-Pei Hong ― Efficient sanitization of informative association rules‖ ACM , Expert Systems with Applications: An International Journal, Volume 35, Issue 1-2, July, 2008 [7] Chih-Chia Weng; Shan-Tai Chen; Hung-Che Lo, ―A Novel Algorithm for Completely Hiding Sensitive Association Rules‖, IEEE Intelligent Systems Design and Applications, 2008.,vol 3, pp.202-208, 2008 [8] Modi, C.N.; Rao, U.P.; Patel, D.R., ―Maintaining privacy and data quality in privacy preserving association rule mining‖, IEEE 2008 Seventh International Conference on Machine Learning and Applications, pp 1-6, 2010


PPDM, Support, Confidence, Information security.

This work is licensed under a Creative Commons Attribution 3.0 Unported License.   

Facebook IconYouTube IconTwitter IconVisit Our Blog