Diffusion Models (DMs) are emerging as powerful generative AI tools for detecting anomalies in increasingly complex, high-dimensional data across critical sectors.

Key applications and benefits:

• Enhanced cybersecurity through advanced detection of unusual patterns or behaviors
• Improved healthcare monitoring by identifying medical anomalies in complex patient data
• Strengthened fraud detection with more sophisticated pattern recognition capabilities
• Manufacturing quality control through precise identification of production anomalies

For security professionals, these models offer next-generation capabilities to identify subtle deviations that might indicate breaches, threats, or vulnerabilities in highly complex systems and networks.

A Survey on Diffusion Models for Anomaly Detection