CAT 530 - Introduction to Artificial Intelligence for Cybercrime Units

Course Description

This course covers the fundamentals of artificial intelligence (AI) and its growing role in cybercrime investigations and criminal activity. Students are introduced to how AI technologies can be used by offenders to support fraud, social engineering, automation, impersonation, and deepfake-enabled activity, as well as how investigators can responsibly use AI-enabled tools to support research, triage, analysis, and reporting. The course emphasizes the limitations and risks of AI, including bias, inaccurate or fabricated outputs, verification requirements, and appropriate documentation and disclosure. Students can expect hands-on cyber range exercises involving the evaluation of AI-generated content and threats, use of AI tools to assist investigative research, verification of AI-supported findings, and application of human review procedures in realistic investigative scenarios.

Course Details

By the completion of this course, successful students will be able to:

Skills Acquired:

• Understanding of how AI is used in cybercrime and investigations
• Ability to recognize common AI-enabled threats and fraud techniques
• Knowledge of responsible and ethical use of AI tools in investigative work
• Skills in verifying AI-assisted outputs against reliable sources
• Ability to document AI-supported investigative activity appropriately

Course Components:
Lectures (Theory Component):

• Introduction to Artificial Intelligence in Cybercrime Contexts
• AI-Enabled Threats, Fraud, Social Engineering, and Deepfakes
• Responsible Use of AI Tools by Investigators
• Prompting, Search Assistance, Summarization, and Analytical Support
• Risks, Biases, Hallucinations, and Verification Requirements
• Documentation, Disclosure, and Operational Considerations

Cyber Range-Based Labs (Hands-On Component):

• Evaluating AI-Generated Threats, Content, and Deepfake Indicators
• Using AI Tools to Support Investigative Research and Triage
• Drafting and Verifying Investigative Summaries
• Identifying Risks in AI-Assisted Analysis
• Applying Human Review and Source Verification Procedures