Harnessing AI & ML for Smarter Cybersecurity

As cyber threats grow more sophisticated, agencies must move beyond static defenses to intelligence-driven security. And while AI and machine learning (ML) enhance efficiency by detecting anomalies, forecasting risks, and accelerating response, agencies still need to address concerns about verification of alert evidence and suggested response actions.

AI-powered security integrates with existing tools like Security Information and Event Management (SIEM) platforms, ticketing systems, and segmentation tools, ensuring alerts are backed by verifiable evidence. By reducing false positives and prioritizing critical threats, AI helps analysts work faster, decreasing mean time to resolution while keeping analysts in control to verify alerts, determine the best course of action and maintain oversight.

Learning Objectives:

• Review the concept of proactive defense and its elements, including threat hunting, penetration testing, and employee training
• Delineate the distinctions between AI and machine learning, and the role that each one plays in strengthening system security
• Outline the tools and techniques that can be enhanced through the use of AI/ML