Extended Distributed RK- Secure Sum Protocol in Apriori Algorithm for Privacy Preserving
Meera Treesa Mathews1, Manju E.V2
1Meera Treesa Mathews, Department of Computer Science and Engineering Sathyabama University Chennai, India.
2Manju E.V, Department of Computer Science and Engineering Sathyabama University Chennai, India.
Manuscript received on March 24, 2014. | Revised Manuscript received on April 14, 2014. | Manuscript published on April 30, 2014. | PP: 85-88  | Volume-3, Issue-4, April 2014. | Retrieval Number:  D2826043414/2013©BEIESP

Open Access | Ethics and Policies | Cite
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Secure sum computation is a simple example of Secure Multi party Computation. This provide privacy to data in case more than two parties are present, while finding combined results of individual data. Association rule mining algorithms like Apriori are used for mining frequent items from database. In this paper we address secure mining of frequent items from a horizontally partitioned data. It uses Apriori algorithm for mining frequent items with the help of a Extended Distributed Rk- Secure Sum Protocol for privacy preserving.
Keywords: Secure sum computation, secure multi party computation, Apriori, Extended Distributed Rk- secure sum protocol, frequent items, Global support.