Hiding Sensitive Patterns in Association Rules Mining

Data mining techniques have been developed in many applications. However, it also causes a threat to privacy. We investigate to find an appropriate balance between a need for privacy and information discovery on association patterns. In this paper, we propose an innovative technique for hiding sensitive patterns. In our approach, a sanitization matrix is defined. By multiplying the original transaction database and the sanitization matrix, a new database, which is sanitized for privacy concern, is gotten. Moreover, a set of experiments is performed to show the effectiveness of our approach.

• Type: Conference
• Year: 2004
• Where: COMPSAC
• Authors: Guanling Lee, Chien-Yu Chang, Arbee L. P. Chen
• Keywords: COMPSAC 2004, Data Mining Techniques, Original Transaction Database, Sanitization Matrix, Software Engineering