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Found 4 papers, 0 papers with code
Discovering Command and Control Channels Using Reinforcement Learning
Command and control (C2) paths for issuing commands to malware are sometimes the only indicators of its existence within networks.
Exposing Surveillance Detection Routes via Reinforcement Learning, Attack Graphs, and Cyber Terrain
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).
Lateral Movement Detection Using User Behavioral Analysis
Lateral Movement refers to methods by which threat actors gain initial access to a network and then progressively move through said network collecting key data about assets until they reach the ultimate target of their attack.
Discovering Exfiltration Paths Using Reinforcement Learning with Attack Graphs
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.
