AI in Cybersecurity Serious Games and Training Platforms: A Systematic Review with an Illustrative AI-Based Reverse Turing Game

Authors

  • Bilgin Metin Management Information Systems Department, Bogazici University, Turkey https://orcid.org/0000-0002-5828-9770
  • Tuncay Avci Management Information Systems Department, Bogazici University, Turkey
  • Atakan Yeşilkayali Management Information Systems Department, Bogazici University, Turkey
  • Hikmet Sami Karaca Management Information Systems Department, Bogazici University, Turkey https://orcid.org/0009-0008-1855-8906
  • Ali Nehir Dündar Management Information Systems Department, Bogazici University, Turkey https://orcid.org/0009-0004-7002-0266
  • Martin Wynn School of Business, Computing and Social Sciences, University of Gloucestershire, UK https://orcid.org/0000-0001-7619-6079

DOI:

https://doi.org/10.47852/bonviewAIA62027173

Keywords:

artificial intelligence, cybersecurity serious games, training platforms, reverse Turing test, Turing test

Abstract

The use of artificial intelligence (AI) in cybersecurity serious games and training platforms is an innovative approach, which enhances the effectiveness of security training by improving the development of practical skills. Numerous studies have focused on the potential of AI-enhanced serious games, highlighting the flexibility and adaptability of this form of education in the cybersecurity domain. The overall aim of this study is to map out the AI technology landscape relevant to cybersecurity games and assess relevant theory and pedagogical frameworks. First, a systematic review of publications from 2019 to 2025 is performed to identify the primary AI techniques and technologies adopted in cybersecurity and to find those relevant to serious games and training platforms. Then, the factors that contribute to their success and the barriers that affect their implementation in game-based environments are analyzed, together with the theoretical frameworks and pedagogical models that support the design of AI-enhanced training platforms. As an illustrative example of these results, an AI-based reverse Turing game is presented. The article will be of interest to those who design cybersecurity games and also to educators who are trying to create training formats that are effective in responding to the fast-changing cybersecurity environment. 

 

Received: 12 August 2025 | Revised: 25 May 2026 | Accepted: 26 June 2026

 

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work. 

 

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study. 

 

Author Contribution Statement

Bilgin Metin: Investigation, Resources, Writing – review & editing, Supervision, Project administration. Tuncay Avci: Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization. Atakan Yeşilkayali: Investigation, Resources, Data curation, Writing–original draft, Writing – review & editing, Visualization. Hikmet Sami Karaca: Investigation, Resources, Data curation. Ali Nehir Dündar: Investigation, Resources, Data curation. Martin Wynn: Writing – review & editing, Supervision.


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Published

2026-07-20

Issue

Online First

Section

Review

License

Copyright (c) 2026 Authors

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Metin, B., Avci, T., Yeşilkayali, A., Karaca, H. S., Dündar, A. N., & Wynn, M. (2026). AI in Cybersecurity Serious Games and Training Platforms: A Systematic Review with an Illustrative AI-Based Reverse Turing Game. Artificial Intelligence and Applications. https://doi.org/10.47852/bonviewAIA62027173