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.
Authors
- Fabrizio Carmignani (ORCID: https://orcid.org/0000-0002-8445-2818)
- Ka Ching Chan (ORCID: https://orcid.org/0000-0002-8756-2991)
- Raj Gururajan (ORCID: https://orcid.org/0000-0002-5919-0174)
Institutions
- University of Southern Queensland (AU)
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