Privacy and security in the big data paradigm

被引:27
|
作者
Sun, Zhaohao [1 ]
Strang, Kenneth David [2 ]
Pambel, Francisca [1 ]
机构
[1] PNG Univ Technol, Dept Business Studies, Lae 411, Morobe, Papua N Guinea
[2] SUNY, Sch Business & Econ, Queensbury, NY USA
关键词
Big data; big data paradigm; privacy and security; healthcare; exponential Weibull trend; big data analytics; PUBLIC-HEALTH; MANAGEMENT; ANALYTICS; ISSUES;
D O I
10.1080/08874417.2017.1418631
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Privacy and security in the big data age have drawn significant attention in the academia and industry. This article examines privacy and security in the big data paradigm through proposing a model for privacy and security in the big data age and a classification of big data-driven privacy and security. It extends the big data body of knowledge, highlights important research topics, and identifies critical gaps through statistical analysis of big data and its impacts on privacy and security based on literature data published from 1916 to 2016. It also presents the state-of-the-art privacy and security based on the analysis of SCOPUS data from 2012 to 2016. The result shows that privacy and security face new challenges and require new policies, technologies, and tools for protecting privacy in the big data paradigm. The proposed approach might facilitate the research and development of privacy and security, and big data-driven privacy and security in terms of technology, governance, and policy development.
引用
收藏
页码:146 / 155
页数:10
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