International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

PPHOPCM: Privacy-preserving High-order Possibilistic c-Means Algorithm for Big Data Clustering with Cloud Computing

Author : C Arun Kumar ¹ Dasari Nishanth Reddy ² Keerthana K N ³ M Sai Chakradhar Reddy ⁴

Date of Publication :21st June 2018

Abstract: PCM is one of the methods used for C means clustering process in which there are two types of clustering, normal PCM clustering and important is high order PCM for big data clustering. The HOPCM method based on Map reduces for the large amount of the heterogeneous data is used. Finally a privacy preserving high-order possibilistic c-means algorithm to protect the private data on cloud by applying the background verification scheme to HOPCM a high-order PCM algorithm to tackle big data clustering by making the objective function minimal in the tensor space. Clustering is designed to separate objects into several different groups according to special metrics, making the objects with similar features in the same group. Clustering techniques have been successfully applied to knowledge discovery and data engineering. With the increasing popularity of big data, big data clustering is attracting much attention from data engineers and researchers

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