Empowering Professionals: A Generative AI Approach to Personalized Cybersecurity Learning

Kallonas, Christos, Piki, Andriani orcid iconORCID: 0000-0003-0376-1713 and Stavrou, Eliana (2024) Empowering Professionals: A Generative AI Approach to Personalized Cybersecurity Learning. 2024 IEEE Global Engineering Education Conference (EDUCON) . pp. 1-10. ISSN 2165-9559

[thumbnail of AAM] PDF (AAM) - Accepted Version
Restricted to Repository staff only

274kB

Official URL: https://doi.org/10.1109/EDUCON60312.2024.10578894

Abstract

We are navigating an era of ongoing technological transformations characterized by a growing need for developing digital skills, including cybersecurity and Artificial Intelligence (AI) literacy. The skills gap in cybersecurity has been acknowledged by the academic and business community at large, which faces an ongoing challenge in terms of finding and attaining talents. Even though different initiatives have been launched to upskill and reskill individuals, they are either ineffective in developing the required competencies or fail to motivate participants to learn and advance their competencies in relation to a cybersecurity job role. A key factor hindering these efforts is the adoption of a generic training approach rather than tailoring learning to the needs of individual learners. It is imperative to identify novel ways to motivate and engage learners, fostering a lifelong learning mindset that is essential for cybersecurity professional development and progression. This work aims to investigate how generative AI can be leveraged to empower professionals to take ownership of their learning by assisting them to create a personalized cybersecurity study plan. The objective is to inspire the design of innovative solutions focusing on accelerating skills development and contributing to increasing the supply of skilled cybersecurity professionals.


Repository Staff Only: item control page