Applied AI Security Synthesis

This unit synthesizes key takeaways from prior lessons to bridge conceptual knowledge and hands-on practice in AI and cybersecurity. Students will apply threat modeling, implement controls in lab scenarios, and evaluate mitigation effectiveness to prepare for the culminating capstone unit.

Learning Objectives

• Analyze consolidated key takeaways to identify at least five vulnerabilities or attack vectors in a provided AI-enabled system
• Apply a recognized threat-modeling framework to produce a prioritized risk assessment with at least three actionable mitigations for the target system
• Demonstrate implementation and testing of at least two technical or procedural security controls (e.g., input validation, access controls, model hardening, logging) in a lab environment and document results
• Evaluate the effectiveness of applied mitigations using measurable criteria (e.g., reduction in attack surface, detection time, false positive rate) and produce recommendations for an incident response and hardening plan