Towards e-learning security: A machine learning approach

Abstract

E-learning allows us to learn anywhere, any place and any time as long as there is access to a configured computer system. E-learning can be network-based, intranet-based, internet-based, cd/dvd-based. It can include audio, video, text, animation and virtual environments. However, the increase of e-learning tools by allowing the creation learning environments does create loop holes for security bridges such as: inadequate authentication for online assessments, identity theft, and impersonation. We propose a new framework that can reduce the security risks, and provide an intelligent e-learning preventive mechanism (IEPM) to identify users' pattern of behaviour in order to determine the level of risks and recommend preventive measures.