GPT-Enabled Cybersecurity Training: A Tailored Approach for Effective Awareness

Nabil Al-Dhamari; Nathan Clarke

doi:10.1007/978-3-031-62918-1_1

GPT-Enabled Cybersecurity Training: A Tailored Approach for Effective Awareness

Nabil Al-Dhamari, Nathan Clarke^*

^*Corresponding author for this work

University of Plymouth

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings published in a book › peer-review

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Abstract

This study explores the limitations of traditional Cybersecurity Awareness and Training (CSAT) programs and proposes an innovative solution using Generative Pre-Trained Transformers (GPT) to address these shortcomings. Traditional approaches lack personalization and adaptability to individual learning styles. To overcome these challenges, the study integrates GPT models to deliver highly tailored and dynamic cybersecurity learning experiences. Leveraging natural language processing capabilities, the proposed approach personalizes training modules based on individual trainee profiles, helping to ensure engagement and effectiveness. An experiment using a GPT model to provide a real-time and adaptive CSAT experience through generating customized training content. The findings have demonstrated a significant improvement over traditional programs, addressing issues of engagement, dynamicity, and relevance. GPT-powered CSAT programs offer a scalable and effective solution to enhance cybersecurity awareness, providing personalized training content that better prepares individuals to mitigate cybersecurity risks in their specific roles within the organization.

Original language	English
Title of host publication	Information Security Education - Challenges in the Digital Age - 16th IFIP WG 11.8 World Conference on Information Security Education, WISE 2024, Proceedings
Editors	Lynette Drevin, Wai Sze Leung, Suné von Solms
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	3-20
Number of pages	18
ISBN (Print)	9783031629174
DOIs	https://doi.org/10.1007/978-3-031-62918-1_1
Publication status	Published - 11 Jun 2024
Event	16th World Conference on Information Security Education, WISE 2024 - Edinburgh, United Kingdom Duration: 12 Jun 2024 → 14 Jun 2024

Publication series

Name	IFIP Advances in Information and Communication Technology
Volume	707
ISSN (Print)	1868-4238
ISSN (Electronic)	1868-422X

Conference

Conference	16th World Conference on Information Security Education, WISE 2024
Country/Territory	United Kingdom
City	Edinburgh
Period	12/06/24 → 14/06/24

ASJC Scopus subject areas

Information Systems and Management

Keywords

Cybersecurity Awareness Training (CSAT)
Generative Pre-Trained Transformers (GPT)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-031-62918-1_1

GPT-Enabled Cybersecurity TrainingAccepted author manuscript, 799 KB

Cite this

Al-Dhamari, N., & Clarke, N. (2024). GPT-Enabled Cybersecurity Training: A Tailored Approach for Effective Awareness. In L. Drevin, W. S. Leung, & S. von Solms (Eds.), Information Security Education - Challenges in the Digital Age - 16th IFIP WG 11.8 World Conference on Information Security Education, WISE 2024, Proceedings (pp. 3-20). (IFIP Advances in Information and Communication Technology; Vol. 707). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-62918-1_1

Al-Dhamari, Nabil ; Clarke, Nathan. / GPT-Enabled Cybersecurity Training : A Tailored Approach for Effective Awareness. Information Security Education - Challenges in the Digital Age - 16th IFIP WG 11.8 World Conference on Information Security Education, WISE 2024, Proceedings. editor / Lynette Drevin ; Wai Sze Leung ; Suné von Solms. Springer Science and Business Media Deutschland GmbH, 2024. pp. 3-20 (IFIP Advances in Information and Communication Technology).

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abstract = "This study explores the limitations of traditional Cybersecurity Awareness and Training (CSAT) programs and proposes an innovative solution using Generative Pre-Trained Transformers (GPT) to address these shortcomings. Traditional approaches lack personalization and adaptability to individual learning styles. To overcome these challenges, the study integrates GPT models to deliver highly tailored and dynamic cybersecurity learning experiences. Leveraging natural language processing capabilities, the proposed approach personalizes training modules based on individual trainee profiles, helping to ensure engagement and effectiveness. An experiment using a GPT model to provide a real-time and adaptive CSAT experience through generating customized training content. The findings have demonstrated a significant improvement over traditional programs, addressing issues of engagement, dynamicity, and relevance. GPT-powered CSAT programs offer a scalable and effective solution to enhance cybersecurity awareness, providing personalized training content that better prepares individuals to mitigate cybersecurity risks in their specific roles within the organization.",

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Al-Dhamari, N & Clarke, N 2024, GPT-Enabled Cybersecurity Training: A Tailored Approach for Effective Awareness. in L Drevin, WS Leung & S von Solms (eds), Information Security Education - Challenges in the Digital Age - 16th IFIP WG 11.8 World Conference on Information Security Education, WISE 2024, Proceedings. IFIP Advances in Information and Communication Technology, vol. 707, Springer Science and Business Media Deutschland GmbH, pp. 3-20, 16th World Conference on Information Security Education, WISE 2024, Edinburgh, United Kingdom, 12/06/24. https://doi.org/10.1007/978-3-031-62918-1_1

GPT-Enabled Cybersecurity Training: A Tailored Approach for Effective Awareness. / Al-Dhamari, Nabil; Clarke, Nathan.
Information Security Education - Challenges in the Digital Age - 16th IFIP WG 11.8 World Conference on Information Security Education, WISE 2024, Proceedings. ed. / Lynette Drevin; Wai Sze Leung; Suné von Solms. Springer Science and Business Media Deutschland GmbH, 2024. p. 3-20 (IFIP Advances in Information and Communication Technology; Vol. 707).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings published in a book › peer-review

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T1 - GPT-Enabled Cybersecurity Training

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AU - Al-Dhamari, Nabil

AU - Clarke, Nathan

PY - 2024/6/11

Y1 - 2024/6/11

N2 - This study explores the limitations of traditional Cybersecurity Awareness and Training (CSAT) programs and proposes an innovative solution using Generative Pre-Trained Transformers (GPT) to address these shortcomings. Traditional approaches lack personalization and adaptability to individual learning styles. To overcome these challenges, the study integrates GPT models to deliver highly tailored and dynamic cybersecurity learning experiences. Leveraging natural language processing capabilities, the proposed approach personalizes training modules based on individual trainee profiles, helping to ensure engagement and effectiveness. An experiment using a GPT model to provide a real-time and adaptive CSAT experience through generating customized training content. The findings have demonstrated a significant improvement over traditional programs, addressing issues of engagement, dynamicity, and relevance. GPT-powered CSAT programs offer a scalable and effective solution to enhance cybersecurity awareness, providing personalized training content that better prepares individuals to mitigate cybersecurity risks in their specific roles within the organization.

AB - This study explores the limitations of traditional Cybersecurity Awareness and Training (CSAT) programs and proposes an innovative solution using Generative Pre-Trained Transformers (GPT) to address these shortcomings. Traditional approaches lack personalization and adaptability to individual learning styles. To overcome these challenges, the study integrates GPT models to deliver highly tailored and dynamic cybersecurity learning experiences. Leveraging natural language processing capabilities, the proposed approach personalizes training modules based on individual trainee profiles, helping to ensure engagement and effectiveness. An experiment using a GPT model to provide a real-time and adaptive CSAT experience through generating customized training content. The findings have demonstrated a significant improvement over traditional programs, addressing issues of engagement, dynamicity, and relevance. GPT-powered CSAT programs offer a scalable and effective solution to enhance cybersecurity awareness, providing personalized training content that better prepares individuals to mitigate cybersecurity risks in their specific roles within the organization.

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PB - Springer Science and Business Media Deutschland GmbH

Y2 - 12 June 2024 through 14 June 2024

ER -

Al-Dhamari N, Clarke N. GPT-Enabled Cybersecurity Training: A Tailored Approach for Effective Awareness. In Drevin L, Leung WS, von Solms S, editors, Information Security Education - Challenges in the Digital Age - 16th IFIP WG 11.8 World Conference on Information Security Education, WISE 2024, Proceedings. Springer Science and Business Media Deutschland GmbH. 2024. p. 3-20. (IFIP Advances in Information and Communication Technology). doi: 10.1007/978-3-031-62918-1_1

GPT-Enabled Cybersecurity Training: A Tailored Approach for Effective Awareness

Abstract

Publication series

Conference

ASJC Scopus subject areas

Keywords

UN SDGs

Access to Document

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GPT-Enabled Cybersecurity Training: A Tailored Approach for Effective Awareness

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