Bibliographic Details
| Title: |
Integrating AI-based and conventional cybersecurity measures into online higher education settings: Challenges, opportunities, and prospects |
| Authors: |
Medha Mohan Ambali Parambil, Jaloliddin Rustamov, Soha Galalaldin Ahmed, Zahiriddin Rustamov, Ali Ismail Awad, Nazar Zaki, Fady Alnajjar |
| Source: |
Computers and Education: Artificial Intelligence, Vol 7, Iss , Pp 100327- (2024) |
| Publisher Information: |
Elsevier, 2024. |
| Publication Year: |
2024 |
| Collection: |
LCC:Electronic computers. Computer science |
| Subject Terms: |
Higher education, Online education systems, E-learning systems, Cybersecurity, Artificial intelligence, Ethics and privacy, Electronic computers. Computer science, QA75.5-76.95 |
| More Details: |
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. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2666-920X |
| Relation: |
http://www.sciencedirect.com/science/article/pii/S2666920X24001309; https://doaj.org/toc/2666-920X |
| DOI: |
10.1016/j.caeai.2024.100327 |
| Access URL: |
https://doaj.org/article/abbf54cffe78419ab0dc19e0ab417908 |
| Accession Number: |
edsdoj.bbf54cffe78419ab0dc19e0ab417908 |
| Database: |
Directory of Open Access Journals |
