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The Path To Autonomous Cyber Defense

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arxiv 2404.10788 v1 pith:MHBBFREA submitted 2024-04-12 cs.CR cs.AI

Sean Oesch , Phillipe Austria , Amul Chaulagain , Brian Weber , Cory Watson , Matthew Dixson , Amir Sadovnik This is my paper · ORCID
classification cs.CRcs.AI
keywords cyberautonomousdefendersdefensepathableagentsartificial
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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.

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Cited by 1 Pith paper

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  1. Multi-Agent Reinforcement Learning in Cybersecurity: From Fundamentals to Applications

    cs.MA 2025-05 conditional novelty 3.0 of 10

    A narrative survey of multi-agent reinforcement learning for cyber defense, reviewing game-theoretic models, cyber gyms, and applications, concluding MARL is promising but faces scalability and simulation-to-real tran...

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