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。网络物理网络是由网络计算机和通信设备与物理系统（如电网和机器人系统）的加速集成而产生的。尽管这种集成可以通过允许更复杂的监视和控制来提高性能，但它也会增加恶意攻击者可用的访问和影响点的数量，从而使网络容易受到攻击。红队-蓝队情景已被用于定性评估和提高军事和情报组织的安全性。防守（蓝色）队试图高效、安全地运行网络，而攻击（红色）队试图破坏网络运行。该研究将产生基于数学模型的定量红蓝队场景分析方法，以及由电网稳定性和分布式多机器人系统问题引起的说明性场景。对弹性和综合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驱动程序中保护公众健康和安全。尽管最近的研究很有意义，但对网络物理网络弹性的全面理解仍然有限。本项目将探索两队随机动态博弈的特定博弈论框架，以数学方式捕捉红队和蓝队场景中的关键问题。具体而言，该研究将确定网络物理网络中的设备团队如何在给定的情况下进行合作，以最佳地利用信息(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敌对团队的行动，其代理本身仅拥有网络的部分信息。结果还将包括设计信息结构的算法，这些算法知道使用组合优化和凸松弛技术提高网络弹性的内容和时间。理论和计算结果将通过电网和分布式多机器人网络的场景进行说明，验证和完善，并将在仿真软件和多机器人实验试验台上实现。

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.