SaTC: CORE: Small: Data-driven Attack and Defense Modeling for Cyber-physical Systems

现代网络物理系统（CPS），如智能建筑或疫苗存储系统，涉及多个连接的设备（电话、传感器和控制器），这些设备执行多个目标，包括温度或湿度控制。然而，诸如Stuxnet或最近针对工业CPS的Colonial pipeline攻击等攻击暴露了主要漏洞，表明当前安全技术不足以保证CPS的正常运行。该项目将通过主动建模和响应对复杂CPS的持续攻击，特别是在CPS漏洞数据有限的情况下，开发针对智能攻击者的有效响应。使用混合攻击图的概念来捕获离散的和特定于领域的（物理）动态，一种数据驱动的博弈论方法来保护CPS的网络和物理组件是这个项目的重点。三个紧密结合的研究重点将跨越这个项目的范围：(1)使用强化学习（RL）来表征攻击者意图的自动化策略；(2)采用博弈论、强化学习和贝叶斯优化相结合的综合防御方法指导CPS的安全策略；(3)利用智能建筑传感器和执行器的仿真数据进行真实仿真评估和验证。多个应用，包括确保对公共安全具有重大社会影响的关键基础设施和供应链的安全，将从项目成果中受益。将为一名博士生和多名本科生提供参加暑期研究项目的培训机会，特别是来自代表性不足的群体。一些K-12的拓展和教师培训活动，包括动手，互动游戏和防守者和攻击者之间的比赛，将被设计来激励K-12的学生追求科学和工程。密歇根州立大学的非合作博弈论研究生课程将以新的数据驱动的方法来丰富解决游戏的课程。已经创建了一个项目网站（https://github.com/sandeepbanik/Data-Driven-Resilient-Systems），以提供对该项目的所有数据的访问。每一份出版物、论文或报告都将有一组与之相关的网页，用于其中包含的数据图和表格。反过来，这些页面中的每一个都指向包含数据本身、元数据以及重新生成数据所需的所有相关信息的文件。该网站将在奖项结束或与奖项相关的最后一次公开发布（以较晚者为准）之后至少3年保持活跃。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Modern cyber-physical systems (CPS) such as smart buildings or vaccine storage systems involve several connected devices (phones, sensors, and controllers) that perform multiple objectives including temperature or humidity control. However, attacks such as Stuxnet, or the recent Colonial pipeline attack on industrial CPS have exposed major vulnerabilities, demonstrating the inadequacy of current security techniques to guarantee proper functioning of a CPS. An effective response against smart attackers by pro-actively modeling and responding to attacks on a complex CPS at an ongoing basis, especially with limited data on vulnerabilities in the CPS will be developed in this project.Using the concept of hybrid attack graphs to capture discrete and domain-specific (physical) dynamics, a data-driven game-theoretic methodology for securing the cyber and physical components of a CPS is the focus of this project. Three closely integrated research thrusts will span the extent of this project: (1) automated strategies to characterize attacker intent using reinforcement learning (RL); (2) an integrated defense approach to guide the security strategies of the CPS using a novel combination of game theory, RL and Bayesian optimization; and (3) evaluation and validation via realistic simulations with emulated data from sensors and actuators of intelligent buildings.Multiple applications including securing critical infrastructure and supply chains with significant societal impact on public safety will benefit from the project outcomes. Training opportunities for one PhD student and multiple undergraduate students participating in summer research programs, especially from underrepresented groups will be created. Several K-12 outreach and teacher training activities, including hands-on, interactive games and contests between a defender and attacker will be designed to motivate K-12 students to pursue science and engineering. The curriculum of the new graduate course on non-cooperative game theory at MSU will be enriched with new data-driven methods for solving games. A project website has been created (https://github.com/sandeepbanik/Data-Driven-Resilient-Systems) to provide access to all data from this project. Each publication, thesis, or report will have associated with it a set of web pages for the data plots and tables contained therein. In turn, each of these pages will point to files containing the data itself, the metadata and, as relevant, all information needed to regenerate the data. This site will remain active for at least 3 years beyond the end of the award, or the last public release of data associated with the award, whichever is later.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.