A Human–AI Collaborative Framework for Cybersecurity Consulting in Capstone Projects for Small Businesses

This paper proposes a Human-AI collaborative framework for cybersecurity consulting tailored to the needs of small businesses, designed and implemented within a Master of Cybersecurity capstone program. The framework outlines a structured four-stage development model that integrates students into real-world consulting tasks while aligning with academic and industry objectives. Human–AI collaboration is embedded throughout the process, combining generative AI tools and domain-specific AI agents with human expertise to support the design, delivery, and refinement of consulting resources. The four stages include (1) AI agent development; (2) cybersecurity roadmap creation; (3) resource development; and (4) industry application. Each stage supports both development-oriented outputs—such as templates, training materials, and client deliverables—and research-oriented projects that explore design practices, collaboration models, and consulting strategies. This dual-track structure enables iterative learning and improvement while addressing educational standards and the evolving cybersecurity landscape for small businesses. This framework provides a scalable foundation for capstone-based consulting initiatives that bridge academic learning and industry impact through Human–AI collaboration.

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Publication Details

Journal
Journal of Cybersecurity and Privacy
Published
2025-05-07
DOI
https://doi.org/10.3390/jcp5020021
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.28
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article

A Human–AI Collaborative Framework for Cybersecurity Consulting in Capstone Projects for Small Businesses

Fabrizio Carmignani, Ka Ching Chan, Raj Gururajan
1 citations
Journal of Cybersecurity and Privacy
Big Data and Business Intelligence
2.28
article

A Human–AI Collaborative Framework for Cybersecurity Consulting in Capstone Projects for Small Businesses

Fabrizio Carmignani, Ka Ching Chan, Raj Gururajan
article en
1 citations

Abstract

This paper proposes a Human-AI collaborative framework for cybersecurity consulting tailored to the needs of small businesses, designed and implemented within a Master of Cybersecurity capstone program. The framework outlines a structured four-stage development model that integrates students into real-world consulting tasks while aligning with academic and industry objectives. Human–AI collaboration is embedded throughout the process, combining generative AI tools and domain-specific AI agents with human expertise to support the design, delivery, and refinement of consulting resources. The four stages include (1) AI agent development; (2) cybersecurity roadmap creation; (3) resource development; and (4) industry application. Each stage supports both development-oriented outputs—such as templates, training materials, and client deliverables—and research-oriented projects that explore design practices, collaboration models, and consulting strategies. This dual-track structure enables iterative learning and improvement while addressing educational standards and the evolving cybersecurity landscape for small businesses. This framework provides a scalable foundation for capstone-based consulting initiatives that bridge academic learning and industry impact through Human–AI collaboration.

Journal of Cybersecurity and PrivacyVol. 5(2)
University of Southern Queensland (AU)
Openalex Percentile: Top 12%
Big Data and Business Intelligence
2.28
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