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ML-Driven Decision Making in Realistic Cyber Exercises
Manage episode 343982448 series 2487640
Content provided by Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
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.
426 episodes
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Manage episode 343982448 series 2487640
Content provided by Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
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.
426 episodes
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Similar to Software Engineering Institute (SEI) Podcast Series
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