Enhancing Cybersecurity Curriculum Development: AI-Driven Mapping and Optimization Techniques

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Enhancing Cybersecurity Curriculum Development: AI-Driven Mapping and Optimization Techniques

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Enhancing Cybersecurity Curriculum Development: AI-Driven Mapping and Optimization Techniques

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

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

Projekt

<a href="/cs/project/VJ03030003" target="_blank" >VJ03030003: Rozvoj mezinárodních partnerství pro vzdělávání a trénink v kybernetické bezpečnosti</a><br>

Návaznosti

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

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název statě ve sborníku

ARES '24: Proceedings of the 19th International Conference on Availability, Reliability and Security

ISBN

979-8-4007-1718-5

ISSN

—

e-ISSN

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Počet stran výsledku

10

Strana od-do

1-10

Název nakladatele

Association for Computing Machinery

Místo vydání

neuveden

Místo konání akce

Vídeň

Datum konání akce

30. 7. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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