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@inproceedings{1842421,
author = {Macák, Martin and Ošlejšek, Radek and Bühnová, Barbora},
address = {New York, NY, USA},
booktitle = {Proceedings of the 27th ACM Conference on on Innovation and Technology in Computer Science Education Vol. 1 (ITiCSE '22)},
doi = {http://dx.doi.org/10.1145/3502718.3524819},
keywords = {cybersecurity training; CTF game; process mining; data analysis},
howpublished = {elektronická verze "online"},
language = {eng},
location = {New York, NY, USA},
isbn = {978-1-4503-9201-3},
pages = {449-455},
publisher = {Association for Computing Machinery},
title = {Process Mining Analysis of Puzzle-Based Cybersecurity Training},
url = {https://dl.acm.org/doi/10.1145/3502718.3524819},
year = {2022}
}
TY - JOUR
ID - 1842421
AU - Macák, Martin - Ošlejšek, Radek - Bühnová, Barbora
PY - 2022
TI - Process Mining Analysis of Puzzle-Based Cybersecurity Training
PB - Association for Computing Machinery
CY - New York, NY, USA
SN - 9781450392013
KW - cybersecurity training
KW - CTF game
KW - process mining
KW - data analysis
UR - https://dl.acm.org/doi/10.1145/3502718.3524819
N2 - The hands-on cybersecurity training quality is crucial to mitigate cyber threats and attacks effectively. However, practical cybersecurity training is strongly process-oriented, making the post-training analysis very difficult. This paper presents process-mining methods applied to the learning analytics workflow. We introduce a unified approach to reconstruct behavioral graphs from sparse event logs of cyber ranges. Furthermore, we discuss significant data features that affect their practical usability for educational process mining. Based on that, methods of dealing with the complexity of process graphs are presented, taking advantage of the puzzle-based gamification of in-class training sessions.
ER -
MACÁK, Martin, Radek OŠLEJŠEK and Barbora BÜHNOVÁ. Process Mining Analysis of Puzzle-Based Cybersecurity Training. Online. In \textit{Proceedings of the 27th ACM Conference on on Innovation and Technology in Computer Science Education Vol. 1 (ITiCSE '22)}. New York, NY, USA: Association for Computing Machinery, 2022, p.~449-455. ISBN~978-1-4503-9201-3. Available from: https://dx.doi.org/10.1145/3502718.3524819.
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