A Meta-analysis of Big Data Security: How the Government Formulates a Model of Public Information and Security Assurance into Big Data

This study aims to find a model for guaranteeing the security of big data information using a bibliometric analysis approach. The data of this research are 710 international indexed scientific articles (Scopus) in the form of (Article, Book Chapter and Conference Paper). Data was collected using the keyword (“security information”) AND (“assurance big data”) and was limited to 2016 to 2020. Bibliometric indicators, such as citations, were used to identify the overall theme structure. The data analysis phase was carried out with the analysis tools of VOSviewer and NVivo Plus 12 software. The use of VOSviewer will map the main theme trends in the research area so that it can find new literature. The main theme mappings are then integrated in the Nvivo Plus12 software analysis tool, to produce large theme visualizations. The results show that the author, institution, and theme keywords infographics that: Research studies on information security and assurance for big data have an increasing trend in the number of articles in the last five years; The study of information security and assurance for big data based on network analysis reveals four important themes of concern to the authors, meaning intelligence, privacy, access, and smart cities. In addition, the Government’s big data information security model pays more attention to data security and privacy, public, social, and trends through a cyber physical social system.