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

no code implementations • 14 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)

Discovering Command and Control Channels Using Reinforcement Learning

no code implementations • 13 Jan 2024 • Cheng Wang, Akshay Kakkar, Christopher Redino, Abdul Rahman, Ajinsyam S, Ryan Clark, Daniel Radke, Tyler Cody, Lanxiao Huang, Edward Bowen

Command and control (C2) paths for issuing commands to malware are sometimes the only indicators of its existence within networks.

reinforcement-learning Reinforcement Learning (RL)

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

no code implementations • 6 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)