Evaluation of Encryption Algorithms for Privacy Preserving Association Rules Mining

Encryption algorithms used in privacy preserving protocols can be affected on overall performance. In this paper we study several encryption algorithms with two methods of privacy preserving association rule mining on distributed horizontal database (PPARM4, and PPARM3). The first method PPARM4 computes association rules that hold globally while limiting the information shared about each site in order to increase the efficiency. The second method PPARM3 is a modification for PPARM4 based on a semihonest model with negligible collision probability. Common encryption algorithms for the two methods of privacy preserving association rule mining on distributed horizontal database selected based on performance metric. So a performance comparison among five of the most common encryption algorithms: RSA, DES, 3DES, AES and Blowfish with the two privacy methods are presented. The comparison has been conducted by running several encryption settings with the two methods of privacy preserving association rule mining on distributed horizontal database. Simulation has been conducted using Java. Results show that, PPARM3 gives better performance with all encryption algorithms implemented. Also PPARM3 with encryption algorithm DES gives best result with different database sizes. Based on the results we can tune the suitable encryption algorithm from our implementations to the required overall performance.