MACÁK, Martin, Radek OŠLEJŠEK and Barbora BÜHNOVÁ. Applying Process Discovery to Cybersecurity Training: An Experience Report. Online. In 2022 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW). Neuveden: IEEE, 2022, p. 394-402. ISBN 978-1-6654-9560-8. Available from: https://dx.doi.org/10.1109/EuroSPW55150.2022.00047.
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Basic information
Original name Applying Process Discovery to Cybersecurity Training: An Experience Report
Authors MACÁK, Martin (703 Slovakia, guarantor, belonging to the institution), Radek OŠLEJŠEK (203 Czech Republic, belonging to the institution) and Barbora BÜHNOVÁ (203 Czech Republic, belonging to the institution).
Edition Neuveden, 2022 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), p. 394-402, 9 pp. 2022.
Publisher IEEE
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
WWW Permalink to the publisher
RIV identification code RIV/00216224:14330/22:00125678
Organization unit Faculty of Informatics
ISBN 978-1-6654-9560-8
Doi http://dx.doi.org/10.1109/EuroSPW55150.2022.00047
UT WoS 000853211100040
Keywords in English cybersecurity; hands-on training; process mining; data analysis; learning analytics
Tags International impact, Reviewed
Changed by Changed by: doc. RNDr. Radek Ošlejšek, Ph.D., učo 3636. Changed: 3/10/2022 16:37.
Abstract
Quality improvement of practical cybersecurity training is challenging due to the process-oriented nature of this learning domain. Event logs provide only a sparse preview of trainees' behavior in a form that is difficult to analyze. Process mining has great potential in converting events into behavioral graphs that could provide better cognitive features for understanding users' behavior than the raw data. However, practical usability for learning analytics is affected by many aspects. This paper aims to provide an experience report summarizing key features and obstacles in integrating process discovery into cyber ranges. We describe our lessons learned from applying process mining techniques to data captured in a cyber range, which we have been developing and operating for almost ten years. We discuss lessons learned from the whole workflow that covers data preprocessing, data mapping, and the utilization of process models for the post-training analysis of Capture the Flag games. Tactics addressing scalability are explicitly discussed because scalability has proven to be a challenging task. Interactive data mapping and Capture the Flag specific features are used to address this issue.
Links
CZ.02.1.01/0.0/0.0/16_019/0000822, interní kód MU
(CEP code: EF16_019/0000822)
Name: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur (Acronym: C4e)
Investor: Ministry of Education, Youth and Sports of the CR, CyberSecurity, CyberCrime and Critical Information Infrastructures Center of Excellence, Priority axis 1: Strengthening capacities for high-quality research
EF16_019/0000822, research and development projectName: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur
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