Search Results for author: Ryan Clark

Found 6 papers, 0 papers with code

Discovering Command and Control (C2) Channels on Tor and Public Networks Using Reinforcement Learning

no code implementations14 Feb 2024 Cheng Wang, Christopher Redino, Abdul Rahman, Ryan Clark, Daniel Radke, Tyler Cody, Dhruv Nandakumar, Edward Bowen

Results on a typical network configuration show that the RL agent can automatically discover resilient C2 attack paths utilizing both Tor-based and conventional communication channels, while also bypassing network firewalls.

Reinforcement Learning (RL)

Exposing Surveillance Detection Routes via Reinforcement Learning, Attack Graphs, and Cyber Terrain

no code implementations6 Nov 2022 Lanxiao Huang, Tyler Cody, Christopher Redino, Abdul Rahman, Akshay Kakkar, Deepak Kushwaha, Cheng Wang, Ryan Clark, Daniel Radke, Peter Beling, Edward Bowen

Reinforcement learning (RL) operating on attack graphs leveraging cyber terrain principles are used to develop reward and state associated with determination of surveillance detection routes (SDR).

reinforcement-learning Reinforcement Learning (RL)

Discovering Exfiltration Paths Using Reinforcement Learning with Attack Graphs

no code implementations28 Jan 2022 Tyler Cody, Abdul Rahman, Christopher Redino, Lanxiao Huang, Ryan Clark, Akshay Kakkar, Deepak Kushwaha, Paul Park, Peter Beling, Edward Bowen

Reinforcement learning (RL), in conjunction with attack graphs and cyber terrain, are used to develop reward and state associated with determination of optimal paths for exfiltration of data in enterprise networks.

reinforcement-learning Reinforcement Learning (RL)

Using Cyber Terrain in Reinforcement Learning for Penetration Testing

no code implementations16 Aug 2021 Rohit Gangupantulu, Tyler Cody, Paul Park, Abdul Rahman, Logan Eisenbeiser, Dan Radke, Ryan Clark

Reinforcement learning (RL) has been applied to attack graphs for penetration testing, however, trained agents do not reflect reality because the attack graphs lack operational nuances typically captured within the intelligence preparation of the battlefield (IPB) that include notions of (cyber) terrain.

reinforcement-learning Reinforcement Learning (RL)

Cannot find the paper you are looking for? You can Submit a new open access paper.