Sampled Data Driven Attack Detection and Adaptation for Security in Control Systems

该项目旨在为网络攻击弹性控制方法和架构做出贡献，这对电网，医疗，制造，交通和许多其他控制系统的安全运行至关重要。 对现代网络基础设施的恶意攻击是一种日常现象，也是对国家安全和福祉的持续威胁。已经有许多网络攻击渗透到关键的工业控制系统，车辆控制单元，用于导航和控制的GPS系统，航空器自动驾驶仪，电网中的SCADA系统等。在所有这些网络攻击中，目的是欺骗控制和监控机制，并可能导致系统不稳定和故障，从而造成可能具有灾难性的物理损坏。 随着控制系统变得越来越复杂，并且经常包括来自网络空间的组件，其安全性正在产生更大的挑战。 该项目的重点是弹性控制方法的理论进展以及无人机系统的实验安全演示。 它还促进了本科生参与安全控制系统分析和设计的主题。 该项目旨在从控制理论的角度解决控制系统的网络安全问题，以开发适用于安全软件和硬件架构的控制器分析和综合方法，从而准确评估和降低此类攻击的风险。 在实践中，控制器是数字化实现的，物理工厂在连续时间域中进化。采样数据控制的实现产生了对隐形攻击的额外脆弱性，如果忽略这些脆弱性，可能会导致灾难性事件。与感兴趣的攻击相关联的安全性不能仅仅通过鲁棒的控制器设计或标准的安全软件来处理。相反，该项目采取了控制算法与控制器运行的安全软件/硬件平台一起沿着设计的方法，所有这些都在采样数据框架中。 所提出的方案和理论结果将使用无人机进行实验验证。

This project aims to contribute to cyber-attack resilient control methods and architectures, which are critically important to safe operation of power grid, medical, manufacturing, traffic and many other control systems. Malicious attacks on modern time cyber infrastructure have been a daily phenomenon and a constant threat for the nation's security and well-being. There have been numerous cyber-attacks that infiltrated critical industrial control systems, vehicle control units, GPS systems used for navigation and control, air-vehicle autopilots, SCADA systems in the power grid, etc. In all of these cyber-attacks the aim is to deceive the control and monitoring mechanism and potentially lead the system to instability and malfunction, thus causing physical damages that could be of catastrophic nature. As control systems are becoming sophisticated and frequently include components from cyberspace, their security is generating greater challenges. The project focuses on theoretical advancements in resilient control methods as well as experimental safety demonstrations with UAV systems. It also promotes the engagement of undergraduate students with the topic of safe control system analysis and design. This project aims to address cyber-security for control systems from a control theory perspective, in order to develop controller analysis and synthesis methods applicable for secure software and hardware architectures in order to accurately assess and reduce the risks of such attacks. In practice controllers are implemented digitally and physical plants evolve in a continuous-time domain. The sampled-data control implementation generates additional vulnerability to stealthy attacks, which, if ignored, can result in a catastrophic event. Security associated with the attacks of interest cannot be dealt with solely by robust controller design nor by standard security software. Instead this project takes the approach of co-designing the control algorithm along with the secure software/hardware platform on which the controller operates, all in a sampled-data framework. The proposed schemes and theoretical results will be verified experimentally using unmanned aerial vehicles.