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.

翻译：自动网络操作(ACO)涉及在对抗情景下发展蓝队(防御)和红色队(攻击者)决策人员,为了支持应用机器学习算法解决这一问题,并鼓励这一领域的研究人员处理ACO环境下的问题,我们引入CybORG,这是ACO研究的在建健身房。CybORG有一个模拟和模拟环境,具有共同界面,便于快速培训自主队,然后可在现实世界系统中测试。初步测试显示了这一方法的可行性。