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Modeling Penetration Testing With Reinforcement Learning Using Capture-the-Flag Challenges and Tabular Q-Learning by bruttipremium is a document available to read on EtoBox.

This paper explores the application of reinforcement learning (RL) to automate penetration testing (PT) through capture-the-flag (CTF) challenges. It highlights the complexities of modeling PT as RL problems, including issues of obscurity and unimodality, and evaluates various RL techniques to address these challenges. The authors argue that while RL can facilitate model-free learning, some prior knowledge may still be necessary for effective problem-solving in PT.

Author

bruttipremium

Language

EN