Collaborative research: cyberai innovation: cyberbridge: AI-scaffolded interprofessional training infrastructure for cyber incident response

The National Science Foundation Division of Graduate Education awarded North Dakota State University $199,842 on September 1, 2026, to develop CyberBridge, an AI-scaffolded interprofessional training platform for cyber incident response and digital forensics education, under the STEM Education program (CFDA 47.076).

CyberBridge pairs digital forensic examiners and prosecutors in realistic cyber incident scenarios delivered through a web-based platform requiring no specialized hardware. The system integrates curriculum, simulated incidents, and a multi-agent AI architecture that provides domain coaching, collaboration mediation, session orchestration, and trust verification. A collaboration mediation agent identifies vocabulary mismatches, procedural misunderstandings, and evidentiary gaps and delivers adaptive scaffolds informed by the Zone of Proximal Development. The project develops an interprofessional scripted-collaboration model, reusable AI-agent skills, and a Delphi-validated competency framework aligned with the NICE Workforce Framework and American Bar Association standards. A quasi-experimental study will compare CyberBridge performance against domain-siloed tutoring by measuring domain competency, collaboration quality, and AI literacy. Major outputs will be released as open-source resources to support adoption by community colleges, regional universities, and law enforcement academies.

Work is performed in Fargo, North Dakota, with a period of performance extending from September 1, 2026, through August 31, 2029. The award is part of the CyberAI Corps Scholarship for Service (CyberAI SFS) program supporting national cybersecurity workforce education capacity.

Abstract

AI-enabled cyberattacks leave digital evidence that must be translated into legally sound investigations and prosecutions. However, digital forensic examiners and criminal justice professionals often lack opportunities to develop the shared vocabulary, procedures, and evidentiary understanding needed for effective collaboration. This project will address this GAP by developing cyberbridge, an AI-scaffolded training system that pairs future forensic examiners and prosecutors in realistic cyber incident scenarios. Delivered through a web-based platform requiring no specialized hardware, cyberbridge will expand cybersecurity education to criminal justice students and support adoption by community colleges, regional universities, and law enforcement academies. Cyberbridge will integrate curriculum, simulated incidents, and a trustworthy multi-agent AI architecture for domain coaching, collaboration mediation, session orchestration, and trust verification. A collaboration mediation agent will identify vocabulary mismatches, procedural misunderstandings, and evidentiary gaps and provide adaptive scaffolds informed by the zone of proximal development. The project will contribute an interprofessional scripted-collaboration model, reusable AI-agent skills, and a delphi-validated competency framework aligned with the nice workforce framework and american bar association standards. A quasi-experimental study will compare cyberbridge with domain-siloed tutoring by measuring domain competency, collaboration quality, and AI literacy. Major project outputs will be released as open-source resources to support broad institutional adoption and strengthen the national cybersecurity workforce. This project is supported by the cyberaicorps scholarship for service (cyberai SFS) program which funds proposals to increase national capacity to educate and train professionals in artificial intelligence (AI) or cybersecurity, and to support their placement and retention in the cyberai mission of government organizations. The scholarship track funds academic institutions to award scholarships to students in exchange for their government service. The innovation track seeks transformative education proposals in the areas of AI, cybersecurity, or the integration of AI and cybersecurity. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are not planned for this award.