论文标题
半机械人：自动网络运营研究健身房
CybORG: An Autonomous Cyber Operations Research Gym
论文作者
论文摘要
自主网络操作（ACO）涉及对抗场景中的蓝色团队（防守者）和红色团队（攻击者）决策模型。为了支持机器学习算法来解决此问题，并鼓励此类从业者在ACO环境中遇到问题，需要一个合适的健身房（用于实验的工具包）。我们介绍了Cyborg，这是一个正在进行的ACO研究中的工作体育馆。在有效地支持加强学习以通过模拟和仿真培训对抗性决策模型的驱动下，我们的设计与先前的相关工作不同。我们的早期评估提供了一些证据表明，机器人适合我们的目的，并可能为ACO研究推进实用应用。
Autonomous Cyber Operations (ACO) involves the consideration of blue team (defender) and red team (attacker) decision-making models in adversarial scenarios. To support the application of machine learning algorithms to solve this problem, and to encourage such practitioners to attend to problems in the ACO setting, a suitable gym (toolkit for experiments) is necessary. We introduce CybORG, a work-in-progress gym for ACO research. Driven by the need to efficiently support reinforcement learning to train adversarial decision-making models through simulation and emulation, our design differs from prior related work. Our early evaluation provides some evidence that CybORG is appropriate for our purpose and may provide a basis for advancing ACO research towards practical applications.
