Privacy models for big data: a survey. (2016)

• Record Type: Journal Article
• Authors: Victor, Nancy; Lopez, Daphne; Abawajy, Jemal H.
• Is Part Of: International journal of big data intelligence. Volume 3:Number 1(2016)
• Page Start: 61
• Page End: 75
• Publication Date: 2016
• Subjects: 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; Big data -- Periodicals; 005.705
• Languages: English
• ISSNs: 2053-1389

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.