Privacy Preserving K-Means Clustering on Horizontally Distributed Data
Privacy Preserving Data mining (PPDM) is the combination of information security technology and knowledge discovery technology. The aim of Privacy preserving data mining is the extraction of relevant knowledge from large amount of digital data while protecting at the same time sensitive information. Here the proposed method for k-Means Clustering techniques on horizontally partitioned data on different nodes in a privacy preserving manner. The authors use k-Means algorithm as the basis for a communication efficient privacy-preserving clustering on databases that are horizontally partitioned between two parties. Here the propose methods for calculating the distance of objects of two parties in a privacy preserving manner.