Association Rule Hiding for Multi-Relational Database

International Journal of Computer Trends and Technology (IJCTT)          
© 2015 by IJCTT Journal
Volume-30 Number-4
Year of Publication : 2015
Authors : Ms. Chaitrali Chaudhari, Ms.Speril Machado


Ms. Chaitrali Chaudhari, Ms.Speril Machado "Association Rule Hiding for Multi-Relational Database". International Journal of Computer Trends and Technology (IJCTT) V30(4):187-195, December 2015. ISSN:2231-2803. Published by Seventh Sense Research Group.

Abstract -
Association rule hiding is a technique that helps to hide sensitive association rule from being discovered by various association rule mining algorithms and display only non-sensitive association rules that do not help much in inducing knowledge from database. However much of the work done in field of association rule hiding only focuses on hiding association rule from single relation. In real life, a database is typically made up of multiple tables. Very few work focusses on hiding sensitive association rules on multi-relational databases. The proposed application presents a technique for hiding sensitive association rules in data warehouses with star schema by reduction in the support/confidence for the rule by heuristic technique that uses “mining then joining then hiding” approach.

1. Vassilios S. Verykios, “Association rule hiding methods, WIREs Data Mining Knowledge Discovery 2013, 3: 28–36 doi: 10.1002/widm.1082.
2. Suma B. Association Rule Hiding Methodologies: A Survey, International Journal of Engineering Research & Technology (IJERT), ISSN: 2278-0181, Vol. 2 Issue 6, June – 2013.
3. K. Srinivasa Rao* & B. Srinivasa Rao,An Insight in to Privacy Preserving Data Mining Methods, The SIJ Transactions on Computer Science Engineering & its Applications (CSEA), Vol. 1, No. 3, July-August 2013.
4. Dasseni E, Verykios VS, Elmagarmid AK, Bertino E. ―Hiding association rules by using confidence and support. In: Proceedings of the 4th International Workshop on Information Hiding; 2001, 369–383.
5. Verykios VS, Elmagarmid AK, Bertino E, Saygin Y, Dasseni E. Association rule hiding. IEEE Trans Knowledge Data Eng 2004, 16:434–447.
6. E.D.Pontikakis, A.A.Tsitsonis andV.S.Verykios, ―Anexperimental study of distortion-based techniques for association rule hiding, IFIP International Federation for Information Processing, vol.144, pp.325–339, 2004.
7. E.D.Pontikakis, A.A.Tsitsonis andV.S.Verykios,L.Chang ―Efficient Algorithm for distortion and blocking techniques, 2007,85-104.
8. Sun X, Yu PS. A border-based approach for hidingsensitive frequent itemsets. In: Proceedings of the FifthIEEE International Conference on Data Mining; 2005,426–433.
9. Moustakides GV, Verykios VS. A Max-Min approach for hiding frequent item sets. In: Proceedings of the Sixth IEEE International Conference on Datamining— Workshops; 2006, 502–506.
10. Gkoulalas-Divanis A, Verykios VS. An integer programming approach for frequent itemset hiding. International Conference on Information and KnowledgeManagement, Proceedings; 2006, 748–757.
11. Menon S, Sarkar S. Minimizing information loss and preserving privacy. 2007, 53:101–116.
12. N.V Muthu Lakshmi, Dr. K. Sandhya Rani, ―Privacy Preserving Association Rule Mining in Horizontally Partioned Databases using Cryptography Techniques. International Journal of Computer Science and Information Technology. Vol.3 ,2012,3176-3182
13. Shyue-Liang Wang1and Tzung-Pei Hong, Yu-Chuan Tsai, Hung-Yu Kao ―Multi-table Association Rule Hiding. Intelligent Systems Design and Applications (ISDA), 2010, Publisher: IEEE, pages 1298-1302.
14. L. Dehaspe and L. De Raedt. ―Mining Association Rules in Multiple Relations, Proceedings of the 7th International Workshop on Inductive Logic Programming, 125–132. 1997.
15. J.F. Guo, W.F. Bian, and J. Li, ―Multi-relational Association Mining with Guidance of User,Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery, 704-709, 2007.
16. V. C. Jensen, N. Soparkar, ―Frequent Itemset Counting Across Multiple Tables, Proceedings of the 4th Pacific- Asia Conference of Knowledge Discovery and Data Mining, Current Issues and New Applications, 49-61, 2000
17. K.K. Ng, W.C. Fu, K. Wang, ―Mining Association Rules from Stars, Proceedings of the 2002 IEEE InternationalConference on Data Mining, 322-329, 2002.
18. Laurentiu B. Cristofor ―Mining Rules in Single Table and Multiple Table Databases, June 2002.
19. Andreia Silva and Claudia Antunes, ―Pattern Mining on Stars with FP-Growth, Modelling Decisions for Artificial Intelligence, Springer, Volume 6408, 2010, p 175-186.
20. Hai Quoc Le, Somjit Arch, Huy Nguyen ―Association Rule Hiding in Risk Management for Retail Supply Chain Collaboration,Computers in Industry, vol. 64, pp. 776–784, 2013.
21. Hai Quoc Le,Somjit Arch,Huy Nguyen, ―Association rule hiding based on Intersection Lattice, Hindawi Publishing Corporation Mathematical Problems in Engineering Volume 2013, Article ID 210405, 11 pages

datamining, frequent itemsets, hiding, multi-relational, sensitive association rule.