A secure two party hierarchical clustering approach for vertically partitioned data set with accuracy measure

Abstract

Data mining has been a popular research area for more than a decade because of its ability of efficiently extracting statistics and trends from large sets of data. However, there are many applications where the data set are distributed among different parties. This makes the privacy an issue of concern for each individual/ organization. This paper makes an approach towards privacy preserving clustering problem for vertically partitioned data set(VPD). We propose a secure hierarchical clustering algorithm for two parties over vertically partitioned data set with accuracy measure. Each site only learns the final results about the clusters, but nothing about the individual’s data.