The Path To Autonomous Cyber Defense
Oesch, Sean, Austria, Phillipe, Chaulagain, Amul, Weber, Brian, Watson, Cory, Dixson, Matthew, Sadovnik, Amir
–arXiv.org Artificial Intelligence
Abstract---Defenders are overwhelmed by the number and scale of attacks against their networks.This problem will only be exacerbated as attackers leverage artificial intelligence to automate their workflows. We propose a path to autonomous cyber agents able to augment defenders by automating critical steps in the cyber defense life cycle. To avoid being overwhelmed, and complexity. The deep neural nets in order to generalize well across creation of autonomous cyber defense agents is one states. By leveraging deep RL, DeepMind has trained promising approach to automate operations and prevent reinforcement learning algorithms to defeat expert human cyber defenders from being overwhelmed.
arXiv.org Artificial Intelligence
Apr-12-2024
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