CybORG: A Gym for the Development of Autonomous Cyber Agents
This addresses the need for standardized environments to apply machine learning in autonomous cyber operations, though it appears incremental as a work-in-progress tool.
The paper tackles the problem of developing autonomous cyber agents for defense and attack in adversarial scenarios by introducing CybORG, a gym for training and testing these agents, with initial testing showing feasibility.
Autonomous Cyber Operations (ACO) involves the development of blue team (defender) and red team (attacker) decision-making agents in adversarial scenarios. To support the application of machine learning algorithms to solve this problem, and to encourage researchers in this field to attend to problems in the ACO setting, we introduce CybORG, a work-in-progress gym for ACO research. CybORG features a simulation and emulation environment with a common interface to facilitate the rapid training of autonomous agents that can then be tested on real-world systems. Initial testing demonstrates the feasibility of this approach.