Analyzing the Integration of Intrusion Detection Systems in Online Learning Applications as an Anti-Cheat Measure
Mary Jane C. Samonte, Mark Gabriel E. Artista, Argon Stacey M. Oliveros, Nathaniel P. Solivio · 2024
Intrusion Detection Systems (IDS) have been well-known as security measures for governing network traffic within a given space. Implementing such an anti-cheat measure for online learning is evaluated by analyzing its capabilities and limitations. Current software for online examination proctoring has limitations, making them do the task required but not to its fullest. This analysis includes the different forms of IDS as its application and usability differ from specific areas and the several cheating methods being committed online to evaluate the best possible form to be applied. This analysis should serve as a standpoint on implementing IDS to academic learning systems online as such applications perfectly fit what is lacking in the current structure. With this in mind, it can be concluded that integrating systems within an already structured architecture is one of the core points shown in this study, as the security measures IDS can offer to the academic landscape are more than sufficient.