Empowering Professionals: A Generative AI Approach to Personalized Cybersecurity Learning

• Published in: 2024 IEEE Global Engineering Education Conference (EDUCON) pp. 1 - 10
• Main Authors: Kallonas, Christos, Piki, Andriani, Stavrou, Eliana
• Format: Conference Proceeding
• Language: English
• Published: IEEE 08-05-2024
• Subjects: ChatGPT; Computer security; cybersecurity career; Cybersecurity learning; cybersecurity professional development; Engineering profession; Ethics; Focusing; Generative AI; learning autonomy; Navigation; personalized learning; Training
• ISSN: 2165-9567
• DOI: 10.1109/EDUCON60312.2024.10578894

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.