Reinforcement Learning for Autonomous Cyber Defense
Analyzes reinforcement Learning for Autonomous Cyber Defense and evaluates key implications for security practitioners.
Summary
No summary yet — watch the video above, or open it on YouTube.
Related talks
Black Hat USA·40 min
Sara Farmer · David Foster · James Short · Dr Andy Harrison FORS · Ian Miles · Matthew Lacey · Chris Willis · Daniel Harrold · Chris Parry · Gregory Palmer · John H · Tom Wilson · Ryan Heartfield · Mark Dorn · Demian Till · David Rimmer · Samuel Bailey · Peter Haubrick · Jack Stone · Madeline Cheah · Pedro Marques · Alfie Beard · Jonathan Francis Roscoe · Alec Wilson · Ryan Menzies · Marco Casassa Mont · Neela Morarji · Lisa Gralewski · Esin Turkbeyler
Industry experts analyze emerging threats surrounding Reinforcement Learning for Autonomous Resilient Cyber Defense.
Black Hat USA·31 min
Vasilios Mavroudis · Jamie Gawith · Sañyam Vyas · Chris Hicks
Presenters detail vulnerability discovery and exploitation in Deep Backdoors in Deep Reinforcement Learning Agents.
CONFidence·35 min
Jakub Strykowski
Engineers explore architecture and security mechanisms for Jakub Strykowski: Reinforcement Learning może zarówno grać w DOOMa, jak i atakować sieci.