Designing Adaptive Cybersecurity Hands-on Training
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14610%2F22%3A00126841" target="_blank" >RIV/00216224:14610/22:00126841 - isvavai.cz</a>
Výsledek na webu
<a href="https://ieeexplore.ieee.org/document/9962663" target="_blank" >https://ieeexplore.ieee.org/document/9962663</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/FIE56618.2022.9962663" target="_blank" >10.1109/FIE56618.2022.9962663</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Designing Adaptive Cybersecurity Hands-on Training
Popis výsledku v původním jazyce
This Research To Practice Full Paper presents an instructor guide and a tool to improve the creation of cybersecurity hands-on training with adaptive learning support. Adaptive learning uses students' performance and skills to assign suitable tasks to improve their learning experience. While it is well-established in many domains, it is rarely used in operating systems, networking, and cybersecurity. In this paper, we improve and present how to ease the creation and optimization process of adaptive hands-on training by instructors. To the best of our knowledge, this paper is one of the first works investigating the process of creating cybersecurity training with adaptive learning. The training uses metrics such as pre-training assessment and performance during the previous tasks in training to assign suitable tasks for each student. With the help of the developed tool, we demonstrate how metrics settings influence the students' transitions between training tasks. The instructors can easily visualize students' transitions throughout the training. This approach helps the instructors adapt the metrics to predict students' transitions between tasks for each training session. The results from performed simulations show that our tool might increase the efficiency of the adaptive training and students' experience even more. Using the experience from the simulations and past training sessions, we propose the design process for the whole creation of adaptive training. This design process is general enough to be adopted by other domains such as operating systems and networking that may use adaptive learning techniques for their hands-on assignments. We have released the tool and all the software components under an open-source license, so other instructors can freely use and adopt them.
Název v anglickém jazyce
Designing Adaptive Cybersecurity Hands-on Training
Popis výsledku anglicky
This Research To Practice Full Paper presents an instructor guide and a tool to improve the creation of cybersecurity hands-on training with adaptive learning support. Adaptive learning uses students' performance and skills to assign suitable tasks to improve their learning experience. While it is well-established in many domains, it is rarely used in operating systems, networking, and cybersecurity. In this paper, we improve and present how to ease the creation and optimization process of adaptive hands-on training by instructors. To the best of our knowledge, this paper is one of the first works investigating the process of creating cybersecurity training with adaptive learning. The training uses metrics such as pre-training assessment and performance during the previous tasks in training to assign suitable tasks for each student. With the help of the developed tool, we demonstrate how metrics settings influence the students' transitions between training tasks. The instructors can easily visualize students' transitions throughout the training. This approach helps the instructors adapt the metrics to predict students' transitions between tasks for each training session. The results from performed simulations show that our tool might increase the efficiency of the adaptive training and students' experience even more. Using the experience from the simulations and past training sessions, we propose the design process for the whole creation of adaptive training. This design process is general enough to be adopted by other domains such as operating systems and networking that may use adaptive learning techniques for their hands-on assignments. We have released the tool and all the software components under an open-source license, so other instructors can freely use and adopt them.
Klasifikace
Druh
D - Stať ve sborníku
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 statě ve sborníku
2022 IEEE Frontiers in Education Conference (FIE)
ISBN
9781665462440
ISSN
1539-4565
e-ISSN
2377-634X
Počet stran výsledku
8
Strana od-do
1-8
Název nakladatele
IEEE
Místo vydání
Uppsala, Sweden
Místo konání akce
Uppsala
Datum konání akce
1. 1. 2022
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
—