Hiding Sensitive Itemsets at Multiple Support Thresholds without Side Effects - Surendra, H; Mohan, HS (International Journal of Computer Sciences and Engineering, 2019)
Mining Frequent pattern is a common technique of data mining and used as a preliminary step to mine association rules. Some frequent patterns are sensitive as they may disclose confidential information to adversaries and needs to be hidden in the data before sharing. Many of the existing techniques hide sensitive itemsets at a single sensitive support threshold. Also, these techniques generate various side effects and suffer from unexpected information loss. In this paper, a novel approach to hide sensitive itemsets at multiple sensitive support thresholds is proposed. The database is modeled as a set of closed itemsets which are selectively sanitized to hide sensitive itemsets. The proposed Recursive Pattern Sanitization algorithm for Personalized Itemsets Hiding (RPS-PIH) sanitizes the closed itemsets to hide sensitive itemsets at multiple sensitive support thresholds without generating any side effects. The sanitized model represents privacy preserved patterns of the database which may be shared to the third party for further data analysis without disclosing private information. Experimental results indicate that the proposed approach is efficient in hiding sensitive itemsets at multiple sensitive support thresholds. The effectiveness of the proposed approach is measured using popular metrics for side effects and information loss. The proposed approach is effective in reducing information loss and eliminating the generation of side effects compared with existing state-of-the-art techniques.