A Multiagent CyberBattleSim for RL Cyber Operation Agents. (arXiv:2304.11052v1 [cs.CR])

Hardening cyber physical assets is both crucial and labor-intensive.
Recently, Machine Learning (ML) in general and Reinforcement Learning RL) more
specifically has shown great promise to automate tasks that otherwise would
require significant human insight/intelligence. The development of autonomous
RL agents requires a suitable training environment that allows us to quickly
evaluate various alternatives, in particular how to arrange training scenarios
that pit attackers and defenders against each other. CyberBattleSim is a
training environment that supports the training of red …

assets attackers autonomous blue cyber cyber physical defenders development environment general great hardening human insight intelligence labor machine machine learning physical train training