CAREER: Going Beyond Linear Models for Attack Detection and Defense in Control Systems

University Of Texas At Dallas, Richardson TX

Investigators

Abstract

This Faculty Early Career Development (CAREER) project will contribute new knowledge related to the security of automation and control systems. Modern control systems enable automation across industries, from manufacturing to chemical processing, and regulate and monitor critical infrastructure, such as power, water, fuel, and transportation. However, these systems are susceptible to cyber-based attacks that target the computers that operate them. Cyber-based attacks could damage physical infrastructure, compromise safety, and harm the environment. Attack mitigation techniques rely on detecting discrepancies between the reported behavior of a physical process and the behavior predicted based on a model, or digital twin, of the process. However, existing models are often insufficient to capture the complex behavior of real-world applications. This award supports fundamental research for the development of detectors that aptly recognize, deter, and mitigate attacks. It will thus benefit the U.S. economy and society through increased resilience to cyber-attacks. Further, to enable a diversified and integrated workforce capable of meeting the security needs of the nation, this award will develop connections between university and community college students. It will support outreach activities and live demonstrations at local schools and community events to positively impact engineering education and to broaden participation of underrepresented groups in technical fields of study. The sensitivity of model-based detectors is intimately connected with the quality of the model used. To date, work has focused on linear dynamical models, which do not capture the complex behavior of real-world applications. To fill this gap, this award will develop a systematic framework for the security analysis of systems with uncertainty and of switched dynamical models. This research will mathematically characterize the relationship between different sources of uncertainty and detector sensitivity. It will parameterize the impact of a potential attack in terms of the system and detector uncertainty, establishing a vulnerability index based on system and uncertainty characteristics. The research team will act as both attacker and defender to develop new attack vectors that leverage the uncertainty present in systems that switch between different modes of operation. 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.