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Applications of Educational Data Mining and Learning Analytics on Data From Cybersecurity Training

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14610%2F22%3A00125776" target="_blank" >RIV/00216224:14610/22:00125776 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://link.springer.com/article/10.1007/s10639-022-11093-6" target="_blank" >https://link.springer.com/article/10.1007/s10639-022-11093-6</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s10639-022-11093-6" target="_blank" >10.1007/s10639-022-11093-6</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Applications of Educational Data Mining and Learning Analytics on Data From Cybersecurity Training

  • Popis výsledku v původním jazyce

    Cybersecurity professionals need hands-on training to prepare for managing the current advanced cyber threats. To practice cybersecurity skills, training participants use numerous software tools in computer-supported interactive learning environments to perform offensive or defensive actions. The interaction involves typing commands, communicating over the network, and engaging with the training environment. The training artifacts (data resulting from this interaction) can be highly beneficial in educational research. For example, in cybersecurity education, they provide insights into the trainees' learning processes and support effective learning interventions. However, this research area is not yet well-understood. Therefore, this paper surveys publications that enhance cybersecurity education by leveraging trainee-generated data from interactive learning environments. We identified and examined 3021 papers, ultimately selecting 35 articles for a detailed review. First, we investigated which data are employed in which areas of cybersecurity training, how, and why. Second, we examined the applications and impact of research in this area, and third, we explored the community of researchers. Our contribution is a systematic literature review of relevant papers and their categorization according to the collected data, analysis methods, and application contexts. These results provide researchers, developers, and educators with an original perspective on this emerging topic. To motivate further research, we identify trends and gaps, propose ideas for future work, and present practical recommendations. Overall, this paper provides in-depth insight into the recently growing research on collecting and analyzing data from hands-on training in security contexts.

  • Název v anglickém jazyce

    Applications of Educational Data Mining and Learning Analytics on Data From Cybersecurity Training

  • Popis výsledku anglicky

    Cybersecurity professionals need hands-on training to prepare for managing the current advanced cyber threats. To practice cybersecurity skills, training participants use numerous software tools in computer-supported interactive learning environments to perform offensive or defensive actions. The interaction involves typing commands, communicating over the network, and engaging with the training environment. The training artifacts (data resulting from this interaction) can be highly beneficial in educational research. For example, in cybersecurity education, they provide insights into the trainees' learning processes and support effective learning interventions. However, this research area is not yet well-understood. Therefore, this paper surveys publications that enhance cybersecurity education by leveraging trainee-generated data from interactive learning environments. We identified and examined 3021 papers, ultimately selecting 35 articles for a detailed review. First, we investigated which data are employed in which areas of cybersecurity training, how, and why. Second, we examined the applications and impact of research in this area, and third, we explored the community of researchers. Our contribution is a systematic literature review of relevant papers and their categorization according to the collected data, analysis methods, and application contexts. These results provide researchers, developers, and educators with an original perspective on this emerging topic. To motivate further research, we identify trends and gaps, propose ideas for future work, and present practical recommendations. Overall, this paper provides in-depth insight into the recently growing research on collecting and analyzing data from hands-on training in security contexts.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Návaznosti výsledku

  • Projekt

    <a href="/cs/project/EF16_019%2F0000822" target="_blank" >EF16_019/0000822: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur</a><br>

  • Návaznosti

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Ostatní

  • Rok uplatnění

    2022

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název periodika

    Education and Information Technologies

  • ISSN

    1360-2357

  • e-ISSN

    1573-7608

  • Svazek periodika

    27

  • Číslo periodika v rámci svazku

    9

  • Stát vydavatele periodika

    US - Spojené státy americké

  • Počet stran výsledku

    34

  • Strana od-do

    12179-12212

  • Kód UT WoS článku

    000805528800005

  • EID výsledku v databázi Scopus

    2-s2.0-85130845189