A case study for evaluating learners' behaviors from online cybersecurity training platform on digital forensics subject

Abstract

Virtual cybersecurity training platforms play an important role in developing the knowledge and practice skills of students in educational institutions and universities. It helps learners can access virtual laboratories through web interfaces without any geolocation restriction, especially in the Covid-19 pandemic. Furthermore, instructors can monitor and understand learners' behaviors in practice sessions by analyzing actions and logs from the virtual platform. But, to realize this feature, such a platform must gather data during cybersecurity training for data mining tasks. In this paper, we introduce a virtual laboratory platform to facilitate cybersecurity training courses, namely vLab. In addition, we apply clustering analysis to the actions of learners to better understand the capabilities of trainees in resolving given challenges in digital forensics subject. With the built-in behavior analyzer in vLab, instructors can find out the common mistakes, and the reasons for learners' failure results, or identify whether they actually conduct experiments to get answers for digital forensics challenges or not.