AI, Machine Learning and Strengthening Cybersecurity

This event qualifies for 1 CPEs

The federal government is dedicated to advancing U.S. leadership in the research, development and use of artificial intelligence (AI), to promote both national security and economic prosperity. Using AI to improve cybersecurity is a logical target for its implementation. It is especially important as the threat landscape continues to evolve.

The World Economic Forum (WEF) reports that about 1.7 billion IoT devices have been installed to date in North America, a number that is only going to accelerate. Many are IP cameras and network-attached storage (NAS) devices, which frequently are targeted by malicious actors. WEF sees machine learning (ML) and AI algorithms as an important cybersecurity tool to fight this, as they can learn from real-world data, infer patterns from incomplete or behaviorally changed data, and rapidly automate decision-making when threats arise.

View our On Demand webcast as thought leaders from government and industry discuss the cybersecurity challenges facing agencies in effectively investigating and blocking threats in a geographically diverse and fragmented ecosystem.

Speaker and Presenter Information

Ramesh Menon, Chief Technology Officer, Defense Intelligence Agency

Martin Skorczynski, Assistant Director for Emerging Technology & Cybersecurity Research, Innovations Lab / Science Technology Assessment, and Analytics U.S. GAO

Elham Tabassi, Chief of Staff, ITL NIST

Wayne LeRiche, Field CTO, Palo Alto Networks

Tony Waller, Principal Sales Engineer, Security Specialist - Federal, Netscout

Wayne LeRichie, Federal Civilian Field Chief of Technology Officer, Palo Alto

Jane Norris, Moderator & Contributing Editor, FedInsider