Skip to content
ML-Driven Decision Making in Realistic Cyber Exercises episode artwork

Oct 13, 2022 48 min

ML-Driven Decision Making in Realistic Cyber Exercises

from Software Engineering Institute (SEI) Podcast Series Hosted by Dustin Updyke, Thomas Podnar

In this podcast from the Carnegie Mellon University Software Engineering Institute, Thomas Podnar and Dustin Updyke, both senior cybersecurity engineers with the SEI's CERT Division, discuss their work to apply machine learning to increase the realism of non-player characters (NPCs) in cyber training exercises.

Episode details come from the podcast's RSS feed.

Embed this episode

Ready to play

ML-Driven Decision Making in Realistic Cyber Exercises

0:00 48:58

No transcript yet.

Requests help us decide what to transcribe next.

Frequently asked questions

How long is this episode of Software Engineering Institute (SEI) Podcast Series?

This episode is 48 minutes long.

When was this Software Engineering Institute (SEI) Podcast Series episode published?

This episode was published on October 13, 2022.

Can I download this Software Engineering Institute (SEI) Podcast Series episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.