AI Security Model Evaluation
This abstract outlines how modern SOC teams can evaluate AI-driven threat detection systems for precision, explainability, and operational resilience.
Key findings
- Model confidence should be paired with incident context and evidence trails.
- False-positive reduction is strongest when behavioral baselines are continuously tuned.
- Explainability matters for analyst trust, compliance review, and response handoff.