Automated Feedback for Participants of Hands-on Cybersecurity Training

Varování

Publikace nespadá pod Lékařskou fakultu, ale pod Fakultu informatiky. Oficiální stránka publikace je na webu muni.cz.
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ŠVÁBENSKÝ Valdemar VYKOPAL Jan ČELEDA Pavel DOVJAK Ján

Rok publikování 2023
Druh Článek v odborném periodiku
Časopis / Zdroj Education and Information Technologies
Fakulta / Pracoviště MU

Fakulta informatiky

Citace
www Open-access article
Doi http://dx.doi.org/10.1007/s10639-023-12265-8
Klíčová slova cybersecurity education; interactive learning environments; hands-on training; virtual labs; shell commands
Přiložené soubory
Popis Computer-supported learning technologies are essential for conducting hands-on cybersecurity training. These technologies create environments that emulate a realistic IT infrastructure for the training. Within the environment, training participants use various software tools to perform offensive or defensive actions. Usage of these tools generates data that can be employed to support learning. This paper investigates innovative methods for leveraging the trainee data to provide automated feedback about the performed actions. We proposed and implemented feedback software with four modules that are based on analyzing command-line data captured during the training. The modules feature progress graphs, conformance analysis, activity timeline, and error analysis. Then, we performed field studies with 58 trainees who completed cybersecurity training, used the feedback modules, and rated them in a survey. Quantitative evaluation of responses from 45 trainees showed that the feedback is valuable and supports the training process, even though some features are not fine-tuned yet. The graph visualizations were perceived as the most understandable and useful. Qualitative evaluation of trainees' comments revealed specific aspects of feedback that can be improved. We publish the software as an open-source component of the KYPO Cyber Range Platform. Moreover, the principles of the automated feedback generalize to different learning contexts, such as operating systems, networking, databases, and other areas of computing. Our results contribute to applied research, the development of learning technologies, and the current teaching practice.
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