Hybrid Algorithm for Privacy Preserving Association Rule Mining
Ila Chandrakar, Yelipe Usha Rani, Mortha Manasa and Kondabala Renuka
DOI : 10.3844/jcssp.2010.1494.1498
Journal of Computer Science
Volume 6, Issue 12
Problem statement: The objective of the hybrid algorithm for privacy preserving data mining is to hide certain sensitive information so that they cannot be discovered through association rule mining techniques. Approach: The sensitive items whether in Left Hand Side (LHS) or Right Hand Side (RHS) of the rule cannot be inferred through association rule mining algorithms by combining the concept of Increase Support of Left Hand Side (ISL) and Decrease Support of Right Hand Side (DSR) algorithms i.e., by increasing and decreasing the support of the LHS and RHS item of the rule respectively. Results: The efficiency of the proposed approach is compared with alone Increase Support of Left Hand Side (ISL) approach for real databases on the basis of number of rules pruned. Conclusion: The hybrid approach of ISL and DSR algorithms prunes more number of sensitive rules with same number of database scans.
© 2010 Ila Chandrakar, Yelipe Usha Rani, Mortha Manasa and Kondabala Renuka. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.