Available on Demand | May 15, 2025 | 1 Hour | 1 CPE

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.

Featured Speakers:

Mark Hadley, Chief Cybersecurity Researcher, Pacific Northwest National Laboratory

Mark Hadley
Chief Cybersecurity Researcher,
Pacific Northwest National Laboratory
Katerina “Kat” Megas, Program Manager for Cybersecurity, Privacy & AI Initiatives, NIST

Katerina “Kat” Megas
Program Manager for Cybersecurity,
Privacy & AI Initiatives,
NIST
Vivian Richards, Staff Partner Technical Manager, Public Sector, Splunk

Vivian Richards
Staff Partner Technical Manager,
Public Sector, Splunk
Alex Maier, Director, Technical Solutions, August Schell

Alex Maier
Director, Technical Solutions,
August Schell
John Breeden II, Moderator & Contributing Editor, FedInsider

John Breeden II
Contributing Editor,
FedInsider

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