Research Article Open Access

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

Mohammad S. Al Rousan1 and Benedetto Intrigila1
  • 1 Department of Enterprise Engineering, University of Rome "Tor Vergata", Italy

Abstract

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

American Journal of Applied Sciences
Volume 19 No. 1, 2022, 51-67

DOI: https://doi.org/10.3844/ajassp.2022.51.67

Submitted On: 8 November 2021 Published On: 2 May 2022

How to Cite: Al Rousan, M. S. & Intrigila, B. (2022). A Data-Sharing Model to Secure Borders Using an Artificial-Intelligence-Based Risk Engine and Big-Data Concepts. American Journal of Applied Sciences, 19(1), 51-67. https://doi.org/10.3844/ajassp.2022.51.67

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Keywords

  • Risky Passengers
  • Border Security
  • Biometrics
  • Big Data
  • Artificial Intelligence