A Data-Sharing Model to Secure Borders Using an Artificial-Intelligence-Based Risk Engine and Big-Data Concepts

The primary aim of this research is to develop a framework for data management and sharing that will enable countries share complex about known unknown high-risk passengers streamline border-control security processes through the use big analytics Artificial Intelligence (AI). A total 15 semi-structured interviews were used gather qualitative data. thematic analysis approach was analyze interview coded using NVivo 11 qualitative-data-analysis software. Five aggregate dimensions developed, comprising nine themes sub-themes, based on 39 codes emerged from This has several theoretical practical contributions. Primarily, development an AI-based risk engine not only improve how borders are enforced but also lead integration new technology border control, thus boosting securitization, decreasing human factors/error, minimizing border-related crime, helping manage healthcare issues.