P3ARM-t: Privacy-Preserving Protocol for Association Rule Mining with t Collusion Resistance

Abstract

The ability to mine large volumes of distributed datasets enables more precise decision making. However, privacy concerns should be carefully addressed when mining datasets distributed over autonomous sites. We propose a new cryptography-based Privacy-Preserving Protocol for Association Rule Mining with t collusion resistance (P3ARM-t), where t is the threshold of number of colluding sites. P3ARM-t is based on a distributed implementation of the Apriori algorithm. The key idea is to arbitrary assign polling sites to collect itemsets’ supports in encrypted forms using homomorphic encryption techniques. Polling sites are randomly assigned and are different for consecutive rounds of the protocol to reduce the potential for collusion. Our performance analysis shows that P3ARM-t significantly outperforms a leading existing protocol. Moreover, P3ARMt is scalable in the number of sites and the volume of data. The protocol also decreases the potential for collusion for up to t colluding sites.