Fast data mining using association rules in distributed databases

Abstract

Data mining can extract important knowledge from large data collections – but sometimes these collec-tions are split among various parties. Privacy concerns may prevent the parties from directly sharing the data, and some types of information about the data. This pa¬per addresses secure mining of association rules over horizontally partitioned data. The methods incorpo¬rate cryptographic techniques to minimize the infor¬mation shared, while adding little overhead to the min¬ing task.