Evolutions, Risks, and Future Directions of Automated Border Control at International Airports: A Bibliometric Analysis
Keywords:
Automated Border Control, Autogate, Biometrics, Airport Security, Facial Recognition, Smart BorderAbstract
Digital transformation in border management has accelerated the implementation of Automated Border Control (ABC) systems, commonly known as autogates, as part of efforts to strengthen national security. These systems utilize biometric technologies, facial recognition, and artificial intelligence (AI) to enhance the efficiency of immigration inspections. However, their implementation introduces various challenges, including cybersecurity threats, data privacy concerns, human error, and digital border governance issues. This study aims to examine the development of Automated Border Control research and identify emerging risk trends associated with autogate implementation. A bibliometric analysis was conducted on 664 publications indexed in the Scopus database. Using VOSviewer, the study mapped the conceptual structure, thematic clusters, and evolution of the ABC research field. The findings reveal that the literature has evolved from a primary focus on operational efficiency toward more complex issues such as AI-driven surveillance, cybersecurity, and governance risks. Biometrics, facial recognition, security, and e-gates emerged as the dominant research themes. The study concludes that ABC systems represent a strategic socio-technical infrastructure that requires adaptive governance and multidimensional risk management to support digital national security.
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