Design & Development of an Economical and Efficient Protocol for Enhanced Privacy and Security in Distributed Databases

Abstract

We propose a protocol for secure mining of association rules in horizontally distributed databases. The current leading protocol is that of Kantarcioglu and Clifton. Our protocol, like theirs, is based on the Fast Distributed Mining (FDM) algorithm of Cheung et al. which is an unsecured distributed version of the Apriori algorithm. The main ingredients in our protocol are two novel secure multi-party algorithms — one that computes the union of private subsets that each of the interacting players hold and another that tests the inclusion of an element held by one player in a subset held by another. Our protocol offers enhanced privacy with respect to the protocol. In addition, it is simpler and is significantly more efficient in terms of communication rounds, communication cost and computational cost.
KEYWORDS: Classification and Regression Trees (CART); and Chi Square Automatic Interaction Detection (CHAID); Beaver-Micali-Rogaway (BMR); Ben-Or-Goldwasser-Wigderson (BGW); Fast Distributed Mining (FDM)