Privacy Preserving Two-Party Hierarchical Clustering Over Vertically Partitioned Dataset

Animesh Tripathy, Ipsa De

School of Computer Engineering, KIIT University, Bhubaneswar, India.

DOI: 10.4236/jsea.2013.65B006                

Abstract

Data mining has been a popular research area for more than a decade. There are several problems associated with data mining. Among them clustering is one of the most interesting problems. However, this problem becomes more challenging when dataset is distributed between different parties and they do not want to share their data. So, in this paper we propose a privacy preserving two party hierarchical clustering algorithm vertically partitioned data set. Each site only learns the final cluster centers, but nothing about the individual’s data.

Keywords

Data Mining; Privacy; Hierarchical; Clustering

Conflicts of Interest

The authors declare no conflicts of interest.

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