Research Article

A Cyber-Physical Framework for Data Assurance and Emergency Response Readiness in Critical Energy Infrastructure

Authors

  • Folasade Okunlola New Mexico Black Leadership Council, New Mexico, United States

Abstract

The increasing digitization of critical energy infrastructure has amplified the need for integrated frameworks that ensure data reliability and operational readiness during emergencies. This paper proposes a novel Cyber-Physical Data Assurance Framework that unifies data governance, real-time analytics, and emergency coordination across digital and physical systems. The framework is architected into four functional layers—Data, Governance, Analytics, and Interface—each designed to preserve data integrity, enhance situational awareness, and synchronize field operations with control systems. Using systems engineering methodology, the framework was validated through simulations of high-risk scenarios including pipeline ruptures, SCADA cyber intrusions, and industrial fire events. Evaluation results demonstrated a 14.3% increase in data availability, a 21.7% improvement in coordination accuracy, and a 40.4% reduction in response latency relative to legacy systems. The model’s alignment with standards such as NIST SP 800-53, ISO/IEC 27001, and ISA/IEC 62443 reinforces its operational feasibility and compliance posture. This research offers a scalable, standards-compliant solution that bridges the gap between IT governance and emergency response readiness in complex, high-stakes energy environments.

Article information

Journal

Journal of Engineering and Applied Sciences

Volume (Issue)

4 (1)

Pages

1-10

Published

2025-06-22

How to Cite

A Cyber-Physical Framework for Data Assurance and Emergency Response Readiness in Critical Energy Infrastructure. (2025). Journal of Engineering and Applied Sciences, 4(1), 1-10. https://doi.org/10.70560/6ag3wg21

References

Baheti, R., & Gill, H. (2011). Cyber-physical systems. The Impact of Control Technology, 12(1), 161–166.

Folasade, O. (2023). Integrating Emergency Data Management Systems in Energy and Natural Resources Industries. International Journal of Environmental Science and Sustainability, 2(1), 11-16. https://doi.org/10.70560/t6n7fh13

Lee, E. A., Seshia, S. A., & Lee, I. (2017). Introduction to Embedded Systems: A Cyber-Physical Systems Approach (2nd ed.). MIT Press.

Liu, S., Zhang, Y., Wang, M., & Huang, T. (2022). Disaster data management for emergency response: A review and future directions. IEEE Access, 10, 12244–12258. https://doi.org/10.1109/ACCESS.2022.3146592

National Institute of Standards and Technology (NIST). (2020). Framework for Improving Critical Infrastructure Cybersecurity, Version 1.1. https://nvlpubs.nist.gov/nistpubs/CSWP/NIST.CSWP.04162018.pdf

Okunlola, F. (2023). Strategic IT and Data Governance in Energy Operations: Lessons from Field Experience. Shell Internal Report.

Otto, B. (2011). Organizing data governance: Findings from the telecommunications industry and consequences for large service providers. Communications of the AIS, 29, 45–66.

Redman, T. C. (2018). Data Driven: Creating a Data Culture. Harvard Business Review Press.

SANS Institute. (2016). Analysis of the Cyber Attack on the Ukrainian Power Grid. https://ics.sans.org/media/E-ISAC_SANS_Ukraine_DUC_5.pdf

Wan, J., Zhang, D., Zhao, S., Yang, L., & Lloret, J. (2016). Context-aware middleware for smart city applications: A review. IEEE Communications Magazine, 54(6), 102–108. https://doi.org/10.1109/MCOM.2016.7509377

Zhang, T., Wang, M., & Zhou, Y. (2021). Real-time data quality monitoring in cyber-physical emergency systems. IEEE Transactions on Industrial Informatics, 17(12), 8551–8563. https://doi.org/10.1109/TII.2021.3096927

Zhou, Y., & Wang, H. (2022). Trustworthy data in cyber-physical emergency systems: A framework for quality assurance. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52(9), 5407–5416. https://doi.org/10.1109/TSMC.2022.3148825

Zhou, Y., & Wang, M. (2022). Data Quality in Emergency Response Systems: A Framework for Real-Time Assurance in CPS. IEEE Transactions on Industrial Informatics, 18(4), 2675–2687. https://doi.org/10.1109/TII.2021.3126721

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Keywords:

Artificial Intelligence Creativity Design Generative Design Human-AI Collaboration