Conclusions
This article examined privacy and security in big data paradigm through proposing a Boolean model for big data privacy and security, and a classification of big data-driven privacy and security. It highlighted important research topics and identified critical gaps through the statistical analysis of big data and its relationships with privacy and security based on literature data published from 1916 to 2016. It analyzed a significant amount of big data literature and found that privacy and security-related topics accounted for about 2% of the total journal outcomes during 2011–2016. It also provided state-of-the-art privacy and security in the big data age by analyzing the document results searched using SCOPUS and the ACM classification for privacy and security in 2012. 22 It demonstrated that the number of publications in privacy and security in the big data age has been exponentially increasing in the past years since 2012. This implies that big data has a significant impact on the research and development of privacy and security.
In the future work, we will investigate big data-driven privacy and security through looking at the impact of big data on each of them in the proposed classification in terms of technology, governance, and policy development. We will also look at business’s and consumers’ perceptions of privacy and security issues in the healthcare industry in a developing country.
