JCOM_V3_N2_RP1 M. Suresh Babu K.F. Bharati Journal on Computer Science 2347–6141 3 2 1 9 Frequent Itemsets, FDM ,Association Rule Mining, Privacy Preserving Data Mining Data warehouses or databases may store large amount of data. In such databases, much processing power is needed for mining association rules. Therefore the solution used is a distributed system. In data mining, association rules are useful for analyzing and predicting customer behavior. They play an important part in shopping basket data analysis, product clustering, catalogue design and store layout. In this paper, the authors have used a protocol Unifying Lists of Locally Frequent Item sets (UNIFI) [1] for mining association rules in vertically partitioned data. In this Proposed system, the authors have aimed to implement the UNIFI protocol for Association Rule Mining in vertically distributed database. This protocol depends on the Fast Distributed Mining (FDM) algorithm like UNIFI-KC (Kantarcioglu and Clifton) in [6]. FDM is an unsecured version of the apriori algorithm. June - August 2015 Copyright © 2015 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=3544