Date of Publication :7th December 2016
Abstract: The primary goal of data mining is to find out the hidden and essential information from large set of data. Such data is collected from various multiple applications or sites, where the privacy and security are the major concern issues. Such data is available is huge amount so it is very difficult to find out the data and relationship among items. For this problem, Association Rule Mining is one of the solutions of data mining techniques, which can efficiently correlate the items. The output of such technique can be used in many real time applications to take the proper decisions. But the data owner, who shares their data for mutual advantages, wants to secure their data in association rule mining process. Because it can reveal the sensitive data, which might be harmful. Therefore it becomes very challenging task to achieve the security of data while mining the knowledge from it. In recent, various methods has been developed, represents the core idea of privacy preserving association rule mining on shared data. Such methods are comparatively examined in this paper, on the basis of technique, advantages and disadvantages.
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