Artificial intelligence in cybersecurity and education: A bibliometric review of emerging trends and research frontiers

This paper presents a comprehensive bibliometric analysis of scholarly research at the intersection of Artificial Intelligence (AI), cybersecurity, and educational technology covering 2003 to 2025. This analysed 304 peer-reviewed publications, selected from the Scopus database, utilising performance analysis and science mapping techniques with VOSviewer and Bibliometrix. The aim is to reveal emerging trends, key contributors, and collaborative research networks in this fast-evolving field. The findings show a significant upward trajectory in scientific output, with an average annual growth rate of 12%, reflecting a growing interest in digital transformation and the need for cybersecurity in education. Thematic evolution analysis demonstrates a conceptual shift from early focuses such as elearning, information security, and digital classrooms to more advanced and interdisciplinary topics like advanced machine learning (ML), learning analytics and AI & cyber ethics. This study also reveals well-defined research clusters, emphasizing the growing interplay between AI-driven educational innovations, cybersecurity threats, and machine learning applications in educational settings. By mapping the intellectual, social, and thematic structures of this interdisciplinary domain. This study offers critical insights for academics, policymakers, and educational technologists. It guides future research trajectories and policy development, particularly in the higher education sector, where secure, AI-enhanced learning environments are becoming increasingly essential.

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Publication Details

Journal
Sustainable Futures
Published
2026-04-02
DOI
https://doi.org/10.1016/j.sftr.2026.101807
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial intelligence in cybersecurity and education: A bibliometric review of emerging trends and research frontiers

Md. Ataur Rahman, Gokhan Yildirim, Md Sarwar Kamal, Rafiqul Islam
Sustainable Futures
Online Learning and Analytics
article

Artificial intelligence in cybersecurity and education: A bibliometric review of emerging trends and research frontiers

Md. Ataur Rahman, Gokhan Yildirim, Md Sarwar Kamal, Rafiqul Islam
article en

Abstract

This paper presents a comprehensive bibliometric analysis of scholarly research at the intersection of Artificial Intelligence (AI), cybersecurity, and educational technology covering 2003 to 2025. This analysed 304 peer-reviewed publications, selected from the Scopus database, utilising performance analysis and science mapping techniques with VOSviewer and Bibliometrix. The aim is to reveal emerging trends, key contributors, and collaborative research networks in this fast-evolving field. The findings show a significant upward trajectory in scientific output, with an average annual growth rate of 12%, reflecting a growing interest in digital transformation and the need for cybersecurity in education. Thematic evolution analysis demonstrates a conceptual shift from early focuses such as elearning, information security, and digital classrooms to more advanced and interdisciplinary topics like advanced machine learning (ML), learning analytics and AI & cyber ethics. This study also reveals well-defined research clusters, emphasizing the growing interplay between AI-driven educational innovations, cybersecurity threats, and machine learning applications in educational settings. By mapping the intellectual, social, and thematic structures of this interdisciplinary domain. This study offers critical insights for academics, policymakers, and educational technologists. It guides future research trajectories and policy development, particularly in the higher education sector, where secure, AI-enhanced learning environments are becoming increasingly essential.

Sustainable FuturesVol. 11
Aksaray University (TR), Charles Sturt University (AU), Preston University (US), Western Sydney University (AU)
Openalex Percentile: Top 31%
Online Learning and Analytics
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