Abstract—Data mining is the process of extracting useful patterns or knowledge from large databases. However, data mining also poses a threat to privacy and information protection if not done or used properly. Therefore, researchers need to investigate data mining algorithm from a new point of view that is of personal privacy. Many algorithms have been developed to hide association rules discovered from a binary database. But in real applications, data mostly consists of quantitative values. In this paper, we thus propose a fuzzy association rules hiding algorithm for hiding rules discovered from a quantitative database. The proposed algorithm integrates the fuzzy set concepts and Apriori mining algorithm to find useful fuzzy association rules and then hide them using privacy preserving technique. For hiding purpose, we decrease the support of the rule to be hidden by decreasing the support value of item in either Left Hand Side (L.H.S.) or Right Hand Side (R.H.S) of the rule. Experimental results show that the proposed algorithm hides more rules and maintains higher data quality of the released database.
Index Terms—Fuzzy association rules, fuzzy set concepts, privacy preserving data mining, quantitative data.
F. Manoj Gupta is a student of Master of Technology in Computer Science and Engineering at Indian Institute of Technology Roorkee, Uttarakhand, India. (Phone: +919897598924)
S. R. C. Joshi is a professor with Electronics and Computer Engineering department at Indian Institute of Technology Roorkee, Uttarakhand, India..
Cite: Manoj Gupta and R. C. Joshi, "Privacy Preserving Fuzzy Association Rules Hiding in Quantitative Data," International Journal of Computer Theory and Engineering vol. 1, no. 4, pp. 382-388, 2009.