Beyond CAGE: Investigating Generalization of Learned Autonomous Network Defense Policies

This paper was accepted at “Reinforcement Learning for Real Life” workshop at NeurIPS 2022.
Advancements in reinforcement learning (RL) have inspired new directions in intelligent automation of network defense. However, many of these advancements have either outpaced their application to network security or have not considered the challenges associated with implementing them in the real-world. To understand these problems, this work evaluates several RL approaches implemented in the second edition of the CAGE Challenge, a public competition to build an autonomous network defender agent in a…