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A curated list of resources dedicated to reinforcement learning applied to cyber security.

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🚀 Awesome Reinforcement Learning
for Cyber Security

A curated list of resources dedicated to reinforcement learning applied to cyber security. Note that the list includes only work that uses reinforcement learning, general machine learning methods applied to cyber security are not included in this list.

For other related curated lists, see :

Table of Contents

Environments

gym-idsgame

gym-idsgame

CyberBattleSim (Microsoft)

CyberBattleSim
  • CyberBattleSim is an experimentation research platform to investigate the interaction of automated agents operating in a simulated abstract enterprise network environment. The simulation provides a high-level abstraction of computer networks and cyber security concepts. Its Python-based Open AI Gym interface allows for the training of automated agents using reinforcement learning algorithms. Blogpost: (2021) Gamifying machine learning for stronger security and AI models

gym-malware

gym-malware

malware-rl

malware-rl

gym-flipit

gym-flipit

gym-threat-defense

gym-threat-defense

gym-nasim

gym-nasim

gym-optimal-intrusion-response

gym-optimal-intrusion-response

sql_env

sql_env

cage-challenge

cage-challenge-1
  • The first Cyber Autonomos Gym for Experimentation (CAGE) challenge environment released at the 1st International Workshop on Adaptive Cyber Defense held as part of the 2021 International Joint Conference on Artificial Intelligence (IJCAI).
cage-challenge-2
  • The second Cyber Autonomous Gym for Experimentation (CAGE) challenge environment announced at the AAAI-22 Workshop on Artificial Intelligence for Cyber Security Workshop (AICS).
cage-challenge-3
  • The third Cyber Autonomous Gym for Experimentation (CAGE) challenge environment.

ATMoS

ATMoS

MAB-Malware

MAB-malware

ASAP

Autonomous Security Analysis and Penetration Testing framework (ASAP)

Yawning Titan

Yawning Titan

Cyborg

Cyborg

FARLAND

FARLAND (github repository missing)
  • FARLAND is a framework for advanced Reinforcement Learning for autonomous network defense, that uniquely enables the design of network environments to gradually increase the complexity of models, providing a path for autonomous agents to increase their performance from apprentice to superhuman level, in the task of reconfiguring networks to mitigate cyberattacks.

    Paper: (2021) Network Environment Design for Autonomous Cyberdefense

SecureAI

SecureAI

CYST

CYST

Papers

Surveys

Demonstration papers

Position papers

Regular Papers

PhD Theses

Master Theses

Bachelor Theses

Posters

Books

Blogposts

Talks

Miscellaneous

Contribute

Contributions are very welcome. Please use Github issues and pull requests.

List of Contributors

License

LICENSE

Creative Commons

(C) 2021-2023

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