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Abstract
Attribute behavior are identified using the rule mining techniques. Fast Distributed Mining (FDM) algorithm is an unsecured distributed version of the Apriori algorithm. Kantarcioglu and Clifton protocol is used for secure mining of association rules in horizontally distributed databases. Unifying lists of locally Frequent Itemsets Kantarcioglu and Clifton (UniFI-KC) protocol is used for the rule mining process in partitioned database environment. UniFI-KC protocol is enhanced in two methods for security enhancement. Secure computation of threshold function algorithm is used to compute the union of private subsets in each of the interacting players. Set inclusion computation algorithm is used to test the inclusion of an element held by one player in a subset held by another. The distributed mining model is used to fetch attribute behavior under the partitioned database environment. The subgroup discovery process is adapted for partitioned database environment. The system can be improved to support generalized association rule mining process. The system is enhanced to control security leakages in the rule mining process.