A Privacy-Preserving Distributed Method for Mining Association Rules

Abstract

In order to improve the privacy preservation and the mining efficiency, an effective privacy preserving distributed mining algorithm of association rules is proposed in this paper. Combining the advantages of both RSA public key cryptosystem and homomorphic encryption scheme, a model of hierarchical management on the cryptogram is put forward in the algorithm. By introducing cryptogram management server and data mining server in the process of mining, the algorithm quickly generates global K-frequent itemsets using similarity matrix of transactions as well as effectively protects security of sensitive data. As shown in the theoretical analysis and the experimental results, the algorithm can achieve improvements in terms of privacy, accuracy, and efficiency.