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.
Index Terms:
association patterns, privacy preservation, sanitized database, data mining
Citation:
Guanling Lee, Chien-Yu Chang, Arbee L. P. Chen, "Hiding Sensitive Patterns in Association Rules Mining," compsac, vol. 1, pp.424-429, 28th Annual International Computer Software and Applications Conference (COMPSAC'04), 2004