CRII: CPS: Designing Resilient Strategies and Information Structures for Team Games in Cyber-physical Networks

该项目将开发理论和计算工具，以评估和提高网络物理网络的弹性。网络物理网络是通过加速网络计算机和通信设备与物理系统（如电网和机器人系统）的集成而创建的。虽然这种集成可以通过允许更复杂的监视和控制来增强性能，但它也会增加恶意攻击者可用的访问和影响点的数量，从而使网络变得脆弱。红队-蓝队情景已被用于定性评估和改善军事和情报组织的安全。防御（蓝色）团队寻求有效和安全地运行网络，而攻击（红色）团队寻求破坏网络运行。这项研究将产生定量的红队蓝队的情况分析的数学模型的基础上，沿着说明性的情况下，在电力网络的稳定性和分布式多机器人系统的问题。对恢复力和全面缓解策略的基本理解将有助于防止严重的攻击后果，并在网络物理系统的所有应用程序驱动程序中保护公共健康和安全。尽管最近的研究兴趣很大，但对网络物理网络中的弹性的全面了解仍然有限。这个项目将探索一个特定的两队随机动态博弈的博弈论框架，在数学上捕捉红队蓝队场景中的关键问题。具体来说，该研究将确定网络物理网络中的设备团队如何合作，以最佳地利用信息，因为（1）每个设备只有关于网络状态和其他设备动作的部分信息;（2）网络动态和信号流受到随机干扰;（3）网络动态和信号流受制于对抗团队的行为，其代理本身仅具有关于网络的部分信息。研究结果还将包括设计信息结构的算法，这些信息结构知道什么以及何时使用组合优化和凸松弛技术来提高网络弹性。理论和计算结果将通过电力网络和分布式多机器人网络中的场景进行说明，验证和细化，这些场景将在仿真软件和多机器人实验测试平台上实现。

This project will develop theoretical and computational tools to assess and improve resilience in cyber-physical networks. Cyber-physical networks are created by the accelerating integration of networked computers and communication devices with physical systems, such as power grids and robotic systems. Although this integration can enhance performance by allowing more sophisticated monitoring and control, it also renders the network vulnerable by increasing the number of access and influence points available to malicious attackers. Red team-blue team scenarios have been used to qualitatively assess and improve security in military and intelligence organizations. The defending (blue) team seeks to operate the network efficiently and securely while the attacking (red) team seeks to disrupt network operation. The research will yield methodology for quantitative red team-blue team scenario analysis based on mathematical models, along with illustrative scenarios arising from problems in power network stability and distributed multi-robot systems. A foundational understanding of resilience and comprehensive mitigation strategies will help to prevent severe attack consequences and protect public health and safety in all application drivers for cyber-physical systems. Despite significant recent research interest, a complete understanding of resilience in cyberphysical networks remains limited. This project will explore a specific game theoretic framework of two-team stochastic dynamic games that mathematically captures crucial issues in red team-blue team scenarios. Specifically, the research will determine how teams of devices in a cyber-physical network can cooperate to make optimal use of information given that (1) each device has only partial information about the state of the network and actions of other devices; (2) the network dynamics and signal flows are subject to random disturbances; and (3) the networks dynamics and signal flows are subject to actions of adversarial teams, whose agents themselves have only partial information about the network. The results will also include algorithms for designing information structures who knows what and when to improve network resiliency using combinatorial optimization and convex relaxation techniques. The theoretical and computational results will be illustrated, validated, and refined by the scenarios in power networks and distributed multi-robot networks, which will be implemented in simulation software and on a multi-robot experimental testbed.