Enhancing Cybersecurity Curriculum Development: AI-Driven Mapping and Optimization Techniques-Reference-Cited by-同舟云学术

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

Published:2024-07-30 Issue: Volume: Page:1-10
ISSN:
Container-title:Proceedings of the 19th International Conference on Availability, Reliability and Security
language:
Short-container-title:

Author:

Dzurenda Petr¹^ORCID,Ricci Sara¹^ORCID,Sikora Marek¹^ORCID,Stejskal Michal¹^ORCID,Lendák Imre²^ORCID,Adao Pedro³^ORCID

Affiliation:

1. Brno University of Technology, Czech Republic

2. University of Novi Sad, Serbia

3. Instituto Superior Técnico, ULisboa, and Instituto de Telecomunicações, Portugal

Funder

Ministerstvo Vnitra České Republiky

Erasmus+

Fundação para a Ciência e a Tecnologia

Nemzeti Kutatási, Fejlesztési és Innovaciós Alap

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3664476.3670467

Reference19 articles.

1. ilastik: interactive machine learning for (bio)image analysis

2. Gianluca Bontempi, Souhaib Ben Taieb, and Yann-Aël Le Borgne. 2012. Machine learning strategies for time series forecasting. In European business intelligence summer school. Springer, 62–77.

3. Petr Dzurenda and Sara Ricci. 2022. R3.4.1 Mapping the framework to existing courses and schemes. https://rewireproject.eu/wp-content/uploads/2023/03/REWIRE_R3.4.1_Deliverable-v8-Final-EC-Check.pdf

4. ENISA. 2022. European Cybersecurity Skills Framework Role Profiles. https://www.enisa.europa.eu/publications/european-cybersecurity-skills-framework-role-profiles

5. ENISA. 2023. Communication on the Cybersecurity Skills Academy. https://digital-strategy.ec.europa.eu/en/library/communication-cybersecurity-skills-academy

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