CAREER: Foundations of Operational Resilience and Secure Communication for Networked Real-Time Systems

About This Grant

Real-time systems underpin applications such as autonomous vehicles and industrial automation require timely responses to sensor data related to emerging scenarios with a precise coordination. In addition, these real-time applications face significant safety risks due to faulty or even compromised components, or to the interruption of inter-system communication. The project’s novelties center on developing foundational principles that enable multiple real-time systems to carry out coordinated operations correctly and safely with timeliness guarantees. The project's significance and importance lie in the establishment of real-time coordination principles and the creation of new security mechanisms that can be extended to security-critical applications. This project also strengthens the nation’s workforce in network and computer system security through integrated educational activities catered to students in higher education and the public. This project aims to develop a novel architecture called RESONET (REsilient and Secure Operation of NETworked real-time systems) that provides strong fault tolerance and real-time guarantees for real-time multi-systems to carry out coordinated operations. The research is organized into three complementary thrusts. The first thrust focuses on foundational cross-system fault tolerance principles, ensuring that coordinated operations meet timeliness requirements even in the face of component failures. It adopts a layered consensus-based approach enhanced by reinforcement learning that dynamically adapts the consensus parameters to network conditions. The second thrust provides a secure communication layer necessary for the above consensus-based approach by adopting lightweight group authentication and key establishment protocols to secure both intra- and inter-system communications among different components. The third thrust provides the last line of defense by developing an intrusion detection mechanism that can forecast imminent timing violations and detect intrusions and failures. The project uses a drone fleet and an automotive communication network to carry out the validation of developed prototypes and to serve as platforms for hands-on educational activities. All research outcomes and educational materials, including tutorials, presentations, publications, and open-source software, will be made publicly available online. 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.