CAREER: Synthesis and Control of Cyber-Resilient CPS

该项目旨在开发用于综合信息物理系统（CPS）的设计方法，当一组未知的系统组件受到损害时，这些系统可验证地满足给定的安全和性能要求。最近对核设施的入侵和对市政府的勒索软件攻击证明了这种设计方法的必要性，其中对手发现了网络防御中的弱点，这些弱点被用来控制安全关键的物理基础设施。研究计划基于两个应用场景：（i）一组无人驾驶飞行器，它们必须完成高级别任务目标，同时避免在存在虚假和恶意传感器和控制输入的情况下发生碰撞，以及（ii）智能建筑，其中物联网应用程序向建筑物HVAC和其他安全设备发送恶意命令-关键系统。PI将开发算法，以在存在注入任意传感器测量或控制信号的攻击的情况下计算控制策略，破坏传感器或控制消息的可用性，和/或修改控制器设定点。第一个研究重点将通过将控制障碍和控制李雅普诺夫函数的概念扩展到对抗设置来研究和开发非线性系统在攻击下的安全性和可达性的控制策略。第二个推力将研究弹性合成更复杂的任务规范使用的控制算法推力一作为积木。PI将通过开发非线性系统的弹性有限状态抽象来开发新方法，将对抗性网络物理交互建模为随机游戏。将通过近似博弈解的方法来制定政府控制策略。这一推力将调查基于合同的分解算法，用于解决分布式系统中的多个（潜在恶意）决策代理的游戏。 该项目的每一个推力都将通过在两个定制平台上进行实验和测试来验证，即多机器人测试平台和智能建筑模拟框架。该项目将产生模型和算法，以提高CPS的安全性，性能和安全性，包括联网和自动驾驶汽车，工业控制系统，智能交通管理系统，医疗设备和制造CPS。PI将开发“严肃的游戏”，以提高公众的兴趣，同时提供对人类决策的洞察力。该项目中开发的安全控制算法将在PI研究生的监督下由本科顶点学生进行实验。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project seeks to develop design methodologies for the synthesis of cyber-physical systems (CPS) that verifiably satisfy given safety and performance requirements when an unknown set of system components is compromised. The need for such design methodologies is exemplified by recent intrusions into nuclear facilities and ransomware attacks on municipal governments, in which adversaries found weak points in cyber defenses that were leveraged to control safety-critical physical infrastructures. The research plan is grounded on two application scenarios: (i) a group of unmanned vehicles that must complete high-level task objectives while avoiding collisions in the presence of false and malicious sensor and control inputs, and (ii) a smart building in which IoT apps send malicious commands to the building HVAC and other safety-critical systems.The PI will develop algorithms to compute control policies in the presence of attacks that inject arbitrary sensor measurements or control signals, disrupt availability of sensor or control messages, and/or modify controller set points. The first research thrust will investigate and develop control strategies for safety and reachability of nonlinear systems under attack by extending the notions of control barrier and control Lyapunov functions to adversarial settings. The second thrust will investigate resilient synthesis of more complex task specifications using the control algorithms of thrust one as building blocks. The PI will develop novel approaches to model adversarial cyber-physical interactions as stochastic games by developing resilient finite-state abstractions of nonlinear systems. Finite-state control policies will be developed by approximating the game solutions. This thrust will investigate contract-based decomposition algorithms for solving the games in a distributed system with multiple (potentially malicious) decision-making agents. Each thrust of the project will be validated through experimentation and testing on two custom platforms, namely, a multi-robot testbed and a smart building simulation framework. This project will result in models and algorithms to improve safety, performance, and security of CPS including connected and autonomous vehicles, industrial control systems, intelligent traffic management systems, medical devices, and manufacturing CPS. The PI will develop “serious games” to enhance public interest while providing insight into human decision-making. Algorithms for secure control developed in the project will be experimented on by undergraduate capstone students under the supervision of the PI’s graduate students.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.