Enhancing Cybersecurity Curriculum Development: AI-Driven Mapping and Optimization Techniques
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F24%3APU151833" target="_blank" >RIV/00216305:26220/24:PU151833 - isvavai.cz</a>
Result on the web
<a href="https://dl.acm.org/doi/10.1145/3664476.3670467" target="_blank" >https://dl.acm.org/doi/10.1145/3664476.3670467</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3664476.3670467" target="_blank" >10.1145/3664476.3670467</a>
Alternative languages
Result language
angličtina
Original language name
Enhancing Cybersecurity Curriculum Development: AI-Driven Mapping and Optimization Techniques
Original language description
Cybersecurity has become important, especially during the last decade. The significant growth of information technologies, internet of things, and digitalization in general, increased the interest in cybersecurity professionals significantly. While the demand for cybersecurity professionals is high, there is a significant shortage of these professionals due to the very diverse landscape of knowledge and the complex curriculum accreditation process. In this article, we introduce a novel AI-driven mapping and optimization solution enabling cybersecurity curriculum development. Our solution leverages machine learning and integer linear programming optimization, offering an automated, intuitive, and user-friendly approach. It is designed to align with the European Cybersecurity Skills Framework (ECSF) released by the European Union Agency for Cybersecurity (ENISA) in 2022. Notably, our innovative mapping methodology enables the seamless adaptation of ECSF to existing curricula and addresses evolving industry needs and trend. We conduct a case study using the university curriculum from Brno University of Technology in the Czech Republic to showcase the efficacy of our approach. The results demonstrate the extent of curriculum coverage according to ECSF profiles and the optimization progress achieved through our methodology.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/VJ03030003" target="_blank" >VJ03030003: Development of International Partnerships for Education and Training in Cybersecurity</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
ARES '24: Proceedings of the 19th International Conference on Availability, Reliability and Security
ISBN
979-8-4007-1718-5
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
1-10
Publisher name
Association for Computing Machinery
Place of publication
neuveden
Event location
Vídeň
Event date
Jul 30, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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