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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM51682

AI-Based Detection of Anomalous User Behavior in Moodle: A Literature Review on E-Learning Security

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM51682

Volume:

9 |

8 |

Aug 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM51682

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

JKK

Jisha Krishnan K1

DAMS

Dr Arun Mozhi Selvi

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Abstract

The growing reliance on web-based education has positioned Learning Management Systems (LMS) such as Moodle at the center of educational operations. However, this trend exposes institutions to the threat of insider threats, meaning entities such as students, teachers, or administrators. Such threats involve unauthorised behaviour and grade hacking. This review of literature discusses 10 insider threat detection studies from learning contexts, focusing on the integration of user behaviour analytics (UBA) and artificial intelligence (AI). The survey also highlights the need for simulation-based models for normal and malicious behaviour modeling and serves as the basis for an AI-based detection system on LMS platforms like Moodle .

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Cite This Article

Jisha Krishnan K1, Dr Arun Mozhi Selvi, "AI-Based Detection of Anomalous User Behavior in Moodle: A Literature Review on E-Learning Security," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 8, Aug 2025. https://doi.org/10.55041/IJSREM51682

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2/7/2025

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