Poster: Generating Experiences for Autonomous Network Defense
Andrés Molina–Markham, Luis F. Robaina, Akash H. Trivedi, Derek G. Tsui, Ahmad Ridley · 2023
Reinforcement Learning (RL) offers a promising path toward developing defenses for the next generation of computer networks. The hope is that RL not only helps to automate network defenses, but in addition, RL finds novel solutions to defend networks that adapt to deal with the increasing complexity of networks and threats. Despite the promise, existing work applying RL to cybersecurity trains cyber defenders on rigid and narrow problem definitions with small computer networks.