Geospatial Cyber-Physical Risk Assessment of Critical Energy Infrastructure in Essex County, New Jersey

As New Jersey advances towards its 2035 clean energy goal, a critical gap remains in identifying where cyber-physical threats to the grid are most likely to trigger high-impact disruptions. This study addresses the question: where in Essex County do cyber exposure, flood risk, and social vulnerability converge to create high-priority zones for infrastructure hardening? We develop a GIS-based multi-criteria risk model using publicly available data sources including census tract boundaries from NJOGIS and the U.S. Census Bureau, internet-exposed Industrial Control System (ICS) devices identified via Shodan passive scanning, FEMA Digital Flood Insurance Rate Maps, and CDC Social Vulnerability Index data at the census-tract level. Risk scores are generated via weighted linear combination with equal weights applied to each component (33% each) to provide a balanced, transparent assessment. Preliminary analysis reveals exposed ICS devices concentrated in Newark and elevated social vulnerability scores in 62% of Essex County tracts, suggesting non-trivial spatial overlap of vulnerability factors. Final outputs include a composite risk map and statistically significant hotspots identified via Moran's I spatial autocorrelation and Getis-Ord Gi∗ analysis. This work demonstrates how open-source geospatial analytics can bridge academic research, utility operations, and state energy policy, enhancing grid resilience where it matters most.