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

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dc.contributor.authorDzurenda, Petrcs
dc.contributor.authorRicci, Saracs
dc.contributor.authorSikora, Marekcs
dc.contributor.authorStejskal, Michalcs
dc.contributor.authorLendak, Imrecs
dc.contributor.authorAdao, Pedrocs
dc.date.accessioned2025-02-18T11:36:13Z
dc.date.available2025-02-18T11:36:13Z
dc.date.issued2024-07-30cs
dc.description.abstractCybersecurity 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.en
dc.formattextcs
dc.format.extent1-10cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationARES '24: Proceedings of the 19th International Conference on Availability, Reliability and Security. 2024, p. 1-10.en
dc.identifier.doi10.1145/3664476.3670467cs
dc.identifier.isbn979-8-4007-1718-5cs
dc.identifier.orcid0000-0002-4366-3950cs
dc.identifier.orcid0000-0003-0842-4951cs
dc.identifier.orcid0000-0002-2896-2303cs
dc.identifier.other189219cs
dc.identifier.researcheridAAC-8713-2019cs
dc.identifier.researcheridR-6057-2018cs
dc.identifier.scopus56418733600cs
dc.identifier.scopus57126826900cs
dc.identifier.scopus57214778197cs
dc.identifier.urihttps://hdl.handle.net/11012/250055
dc.language.isoencs
dc.publisherAssociation for Computing Machinerycs
dc.relation.ispartofARES '24: Proceedings of the 19th International Conference on Availability, Reliability and Securitycs
dc.relation.urihttps://dl.acm.org/doi/10.1145/3664476.3670467cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectCurricula Designen
dc.subjectECSF frameworken
dc.subjectMethodologyen
dc.subjectCybersecurity Educationen
dc.titleEnhancing Cybersecurity Curriculum Development: AI-Driven Mapping and Optimization Techniquesen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-189219en
sync.item.dbtypeVAVen
sync.item.insts2025.02.18 12:36:13en
sync.item.modts2025.02.13 15:32:05en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav telekomunikacícs
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