Using AI for cybersecurity
Help analysts detect, investigate, and respond faster while keeping evidence, escalation, and accountability visible.
Cybersecurity research and engineering
Greenwood Cyber + AI Lab
We build and evaluate defender tools, data-protection patterns, and test suites that make AI systems safer in production.
Scope
The work follows three risk paths: how defenders use AI, how sensitive data moves through AI systems, and how AI platforms can be attacked.
Help analysts detect, investigate, and respond faster while keeping evidence, escalation, and accountability visible.
Set boundaries for sensitive data across prompts, retrieval, applications, logs, and model outputs.
Find and reduce ways AI systems can be attacked, misused, monitored poorly, or trusted too soon.
Principles
The lab uses AI to support accountable security work and human judgment without letting automation own the outcome.
The lab uses AI to support accountable security work and human judgment without letting automation own the outcome.
Sensitive data boundaries are defined before deployment, including prompts, retrieval, logs, and outputs.
Recommendations need tests, measurements, or enough detail for others to evaluate and reuse the work.
Automation earns scope gradually, with review points, limits, and a path for human intervention.
Systems should fail safely, recover well, and remain observable under pressure.
Featured Work
These examples show the kind of work the lab supports: understand the system, focus the risk, test what matters, and turn findings into practical decisions.
Location
The lab is in a region shaped by energy, aerospace, defense, finance, higher education, and critical infrastructure, making Greenwood a practical base for work on cyber resilience and AI security.

Leadership
The lab’s leaders bring security, engineering, and field experience to projects shaped with customers and partners.

General Manager

Technical Director
Contact
The lab partners with researchers, defenders, educators, students, workforce groups, community organizations, and security teams on practical AI security problems.
Microsoft Forms
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Do not include passwords, sensitive personal data, customer confidential information, or details of an active security incident.
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