https://bampel.com/tag/nist-ir-8473/NIST IR 8473Wowchemy (https://wowchemy.com)en-usSat, 12 Dec 2026 00:00:00 +0000https://bampel.com/media/sharing-card.pnghttps://bampel.com/tag/nist-ir-8473/https://bampel.com/workshop_publication/evcs-conformance-wisp-2026/Sat, 12 Dec 2026 00:00:00 +0000https://bampel.com/workshop_publication/evcs-conformance-wisp-2026/Electric Vehicle Charging Stations (EVCS) are increasingly networked components of transportation and energy infrastructure. However, practical methods for translating observed EVCS data into cybersecurity framework-aligned review priorities remain limited. Existing work often emphasizes attack detection and vulnerability discovery but provides less support for standards-based assessment. This paper proposes a semantic conformance-scoring method that maps EVCS asset profiles to task-level guidance extracted from the Identify function of the EVCS-specific NIST IR 8473 framework. In the absence of gold-standard EVCS-to-NIST labels, the study evaluates candidate models using intrinsic diagnostics, including score behavior, rank stability, cross-model convergence, and ablation analysis. A MiniLM + CTI-BERT consensus model was selected based on these criteria. The final scoring converts 17,325 successfully scored EVCS records into ranked NIST IR 8473 Identify-task review profiles. Results suggest that the workflow can support prioritization of EVCS assets for vendor review and identify relevant task areas for follow-up, while the scores should be interpreted as review-prioritization signals rather than verified compliance findings. This work contributes a scalable, framework-grounded workflow for EVCS cybersecurity assessment.