Title: Privacy models for big data: a survey

Authors: Nancy Victor; Daphne Lopez; Jemal H. Abawajy

Addresses: School of Information Technology and Engineering, VIT University, Vellore, India ' School of Information Technology and Engineering, VIT University, Vellore, India ' Faculty of Science, Engineering and Built Environment, Deakin University, Melbourne, Australia

Abstract: Big data is the next big thing in computing. As this data cannot be processed using traditional systems, it poses numerous challenges to the research community. Privacy is one of the important concerns with data, be it traditional data or big data. This paper gives an overview of big data, the challenges with big data and the privacy preserving data sharing and publishing scenario. We focus on the various privacy models that can be extended to big data domain. A description of each privacy model with its benefits and drawbacks is discussed in the review. This survey will contribute much to the benefit of researchers and industry players in uncovering the critical areas of big data privacy.

Keywords: anonymisation; big data challenges; big data characteristics; big data privacy; differential privacy; k-anonymity; l-diversity; privacy models; privacy preservation; privacy protection; social network graphs; streaming data; t-closeness; data sharing; publishing.

DOI: 10.1504/IJBDI.2016.073904

International Journal of Big Data Intelligence, 2016 Vol.3 No.1, pp.61 - 75

Available online: 29 Dec 2015 *

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