Hiding Sensitive Patterns in Association Rules Mining

  • Authors:
  • Guanling Lee;Chien-Yu Chang;Arbee L. P. Chen

  • Affiliations:
  • National Dong Hwa University;National Dong Hwa University;National Cheng-chi University

  • Venue:
  • COMPSAC '04 Proceedings of the 28th Annual International Computer Software and Applications Conference - Volume 01
  • Year:
  • 2004

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Abstract

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.