This repository is a curated list of resources focused on applying reinforcement learning (RL) to cybersecurity challenges. It serves researchers, engineers, and practitioners interested in leveraging RL for tasks like network defense, penetration testing, and threat detection. The primary benefit is a centralized collection of relevant papers, environments, books, and talks, accelerating research and development in this specialized field.

How It Works

The list categorizes resources into environments, papers, books, blog posts, talks, and miscellaneous items. It highlights specific RL environments designed for cybersecurity, such as CybORG++, CyberShield, Cyberwheel, and PenGym, which provide simulated or emulated environments for training and evaluating RL agents in cyber defense and attack scenarios. The extensive paper list covers a wide range of RL applications, from intrusion detection and prevention to automated penetration testing and malware analysis.

Quick Start & Requirements

This repository is a curated list and does not have a direct installation or execution command. Users are expected to follow links to individual projects, papers, or resources, each with its own setup requirements.

Highlighted Details

• Extensive collection of over 500 papers, 20+ PhD/Master's theses, and numerous talks and blog posts related to RL in cybersecurity.
• Features a comprehensive list of specialized RL environments like CybORG++, CyberShield, Cyberwheel, and PenGym, designed for cybersecurity training and evaluation.
• Includes a detailed breakdown of RL applications across various cybersecurity domains, such as intrusion detection, penetration testing, malware analysis, and network defense.
• Provides links to relevant conferences, workshops, and research groups in the field.

Maintenance & Community

The project is actively maintained, with contributions welcomed via GitHub issues and pull requests. A list of contributors is available, indicating community engagement.

Licensing & Compatibility

The repository itself is licensed under Creative Commons. Individual linked resources will have their own licenses, which may vary.

Limitations & Caveats

As a curated list, the repository's value is dependent on the quality and relevance of the linked external resources. It does not provide direct tooling or code for RL applications in cybersecurity.