A Layered Reference Model for Penetration Testing with Reinforcement Learning and Attack Graphs. (arXiv:2206.06934v1 [cs.CR])

This paper considers key challenges to using reinforcement learning (RL) with
attack graphs to automate penetration testing in real-world applications from a
systems perspective. RL approaches to automated penetration testing are
actively being developed, but there is no consensus view on the representation
of computer networks with which RL should be interacting. Moreover, there are
significant open challenges to how those representations can be grounded to the
real networks where RL solution methods are applied. This paper elaborates on
representation …

attack penetration penetration testing reference testing