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Cited by 35Information and Cyber SecurityNetwork Security and Intrusion DetectionArtificial Intelligence in Education

Integrating AI-based and conventional cybersecurity measures into online higher education settings: challenges, opportunities, and prospects

Open access
Parambil, Medha Mohan Ambali, Rustamov, Jaloliddin, Ahmed, Soha Galalaldin, Rustamov, Zahiriddin, Awad, Ali Ismail, Zaki, Nazar, Alnajjar, Fady·2024·Computers and Education Artificial Intelligence
DOI 10.1016/j.caeai.2024.100327
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Abstract

The rapid adoption of online learning in higher education has resulted in significant cybersecurity challenges. As educational institutions increasingly rely on digital platforms, they are facing cyber threats that can compromise sensitive data and disrupt operations. This systematic literature review explores the integration of artificial intelligence (AI) into traditional methods to address cybersecurity risks in online higher education. The review integrates a qualitative synthesis of relevant literature and a quantitative meta-analysis using PRISMA guidelines, ensuring comprehensive insights into the integration process. The most prevalent cybersecurity threats are examined, and the effectiveness of AI-based and conventional approaches in mitigating these challenges is compared. Additionally, the most effective AI techniques in cybersecurity solutions are analyzed, and their performance is compared across different contexts. Furthermore, the review considers the key ethical and technical considerations associated with integrating AI into traditional cybersecurity methods. The findings reveal that while AI-based techniques offer promising solutions for threat detection, authentication, and privacy preservation, their successful implementation requires careful consideration of data privacy, fairness, transparency, and robustness. The importance of interdisciplinary collaboration, continuous monitoring of AI models—by automated systems and humans—and the need for comprehensive guidelines to ensure responsible and ethical use of AI in cybersecurity are highlighted. The findings of this review provide actionable insights for educational institutions, educators, and students, helping to facilitate the development of secure and resilient online learning environments. The identified ethical and technical considerations can serve as a foundation for the responsible integration of AI into cybersecurity within the online higher-education sector.

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  • Building a strong cybersecurity foundation, as described in cybersecurity education frameworks, ensures that personnel are prepared to handle evolving threats.

    “In addition, building a strong cybersecurity foundation, as described in the cybersecurity education frameworks [109,110], ensures that personnel are prepared to handle evolving threats.”

    From Digital Twins in the IIoT: Current Practices and Future Directions Toward Industry 5.0 (2025) · cites this paper as [109]

    Section 2 (p. 4) reports a need for targeted training and curriculum development for cybersecurity professionals, and Section 5.1.7 (p. 12) says ongoing education and awareness can improve security in educational institutions. The paper does not establish that cybersecurity education frameworks ensure personnel are prepared to handle evolving threats; that guarantee overstates its discussion. (LLM, conf=0.82)

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Research works printed but not linked: 11

  1. Althobaiti, K., Jenkins, A. D. G., & Vaniea, K. (2021). A case study of phishing incident response in an educational organization. In Proceedings of the ACM on human-computer interaction (Vol. 5) . New York, NY, USA: Association for Computing Machinery.
  2. Alwahaibi, A., Bin, W., Hassa, W., Basri, W., Wan Ismail, W., & Almamari, M. (2022). A systematic literature review on IT security standards for higher education institution. Tianjin Daxue Xuebao (Ziran Kexue yu Gongcheng Jishu Ban)/J Tianjin Univ Sci Technol , 55 , 194-213. https://doi .org /10 .17605 /OSF .IO /F935H.
  3. Bhatia, M., & Maitra, J. K. (2018). E-learning platforms security issues and vulnerability analysis. In 2018 international conference on computational and characterization techniques in engineering i& sciences (CCTES) (pp. 276-285).
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  5. Dandotiya, M., Rahi, P., Khunteta, A., Anushya, A., & Ahmad, S. S. (2022). SAFE: A secure authenticated & integrated framework for e-learning. In Proceedings of the 4th international conference on information management & machine intelligence (pp. 1-9).
  6. Ghizlane, M., Hicham, B., & Reda, F. H. (2019). A new model of automatic and continuous online exam monitoring. In 2019 international conference on systems of collaboration big data, Internet of things I& security (SysCoBIoTS) (pp. 1-5).
  7. Higgins, J. P., & Green, S. (2011). Cochrane handbook for systematic reviews of interventions (version 5.1.0 ed.). The Cochrane Collaboration. Retrieved from https:// handbook .cochrane .org.
  8. Ivanova, M., & Ilieva, R. (2021). Towards security, data privacy and learning performance. In 2021 19th international conference on information technology based higher education and training (ITHET) (pp. 1-7).
  9. Minkovska, D., & Ivanova, M. (2021). Security in multimedia information systems: Analysis and prediction. In Methodologies and intelligent systems for technology enhanced learning, 10th international conference. Workshops: Volume 2 (pp. 15-24).
  10. Nyasvisvo, B., & Chigada, J. M. (2023). Phishing attacks: A security challenge for university students studying remotely. The African Journal of Information Systems , 15 (2), 116-140.
  11. Pappalardo, S. M., Niemiec, M., Bozhilova, M., Stoianov, N., Dziech, A., & Stiller, B. (2020). Multi-sector assessment framework-a new approach to analyse cybersecurity challenges and opportunities. In Multimedia communications, services and security: 10th international conference, MCSS 2020, Kraków, Poland, October 8-9, 2020, proceedings 10 (pp. 1-15).

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Authors
Parambil, M. M. A., Rustamov, J., Ahmed, S. G., Rustamov, Z., Awad, A. I., Zaki, N., & Alnajjar, F.
Affiliations
United Arab Emirates University (AE)
Corresponding author
Awad, Ali Ismail
ORCID
Venue
Computers and Education Artificial Intelligence
Publisher
Elsevier BV
Published
2024-12
Volume
7
Pages
100327
ISSN
2666-920X (ISSN-L)
DOI
10.1016/j.caeai.2024.100327
OpenAlex
W4403930942
Cited by
35
References
105
Citations by year
2026: 18 · 2025: 15 · 2024: 2
FWCI
13.19
Type
journal article
Language
en
Open access
Licence
Locations
  • Computers and Education Artificial Intelligence (publishedVersion, cc-by-nc-nd)
  • Lirias (KU Leuven) (submittedVersion, cc-by-nc-nd)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Physical Sciences › Computer Science › Information Systems › Information and Cyber Security
  • Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
Keywords
artificial intelligence in cybersecurity, online higher education, cyber threats, threat detection, authentication, data privacy, AI ethics, responsible AI, interdisciplinary collaboration, online learning security

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