National Geospatial Intelligence Agency’s (NGA) primary focus is to track and locate the movement of specific goods with a special interest in the detection of anomalies in the goods’ movements, which may indicate nefarious activity. NGA analysts need tools that aid them in real-time anomaly detection, including models that describe the complex system of global supply chains from the perspectives of technology, operations, policy, and governance. With these models, current behavior can then be compared in real-time with what is considered “normal” in order to detect anomalies.
This project aims to identify open source and commercially available data sources for modeling movement of goods over the global supply chain infrastructure, build models and pattern recognition algorithms to describe regular global supply chain operations (potentially for a subregion), and design a framework for unexpected movement detection in real time. The developed models and algorithms will be essential to the resilience of the system in that if there is an anomaly, localized targeted actions can be taken without disrupting the entire global system.