This National Science Foundation (NSF) Faculty Early Career Development (CAREER) Project Grant, awarded under the NSF Engineering program (CFDA 47.041), provides $540,362 to the University of Wisconsin System to develop novel methodologies that integrate modeling, detection, and control measures for understanding the cyber-physical resilience of continuous critical manufacturing systems.
The key objectives of this 5-year project include: (1) developing generalizable tools for quantifying cyber-physical resilience by creating stochastic models that integrate IIoT network features and manufacturing system dynamics; (2) rethinking cyber-physical resilience-driven anomaly detection by incorporating system-wide resilience quantification into process-based anomaly detection algorithms; and (3) creating collaborative learning-based resilient control strategies that leverage reinforcement learning and system connectivity to enhance a system's adaptability to cyberattacks. This research aims to eliminate barriers to the development of new policies, regulations, and standards for IIoT applications in manufacturing, with potential for extending the methods and tools to other critical infrastructures to enhance national cyber-physical resilience.
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