Matt McManus

abstract:We are looking to understand the decision processes and factors cyber attackers use to achieve their goals so that defensive measures can be deployed. The complexity of network infrastructure, defensive policies, and the secretive nature of cyber attacks make assessing the behaviors difficult. We hope to explore ML techniques like RL to assist in understanding the different cyber-attack processes. Reinforcement learning leveraging cyber-attack simulation enables us to search for rewarding attacker campaigns; however, this approach has several downsides. This is why we will be exploring the concept of Neuro-Symbolic learning to develop human-interpretable models of deep decision processes so that mitigation efforts can be linked to a specific attacker's decision or behavior.