Auto-SGCR: Automated Generation of Smart Grid Cyber Range Using IEC 61850 Standard Models

Digitalization of power grids have made them increasingly susceptible to cyber-attacks in the past decade. Iterative cybersecurity testing (i.e., red-team testing or penetration testing) is indispensable to counter emerging attack vectors and to ensure dependability of critical infrastructure. Furthermore, these can be used to evaluate cybersecurity configuration, effectiveness of the cybersecurity measures against various attack vectors, and to train smart grid cybersecurity experts defending the system. Facilitating extensive experiments narrows the gap between academic research and production environment. A high-fidelity cyber range (a virtual cybersecurity testbed emulating smart grid systems) is vital as it is often infeasible to conduct such experiments and training using production environment. However, the design and implementation of cyber range requires extensive domain knowledge of physical and cyber aspect of the infrastructure. Furthermore, costs incurred for setup and maintenance of cyber range are significant. Moreover, most existing smart grid cyber ranges are designed as a one-off, proprietary system, and are limited in terms of configurability, accessibility, portability, and reproducibility. To address these challenges, an automated Smart grid Cyber Range generation framework (Auto-SGCR) is presented in this paper. Initially a human-/machine-friendly, XML-based modeling language called Smart Grid Modeling Language (SG-ML) was defined, which incorporates IEC 61850 System Configuration Language (SCL) files. Subsequently, a toolchain to parse SG-ML model files and automatically instantiate a functional smart grid cyber range was developed. The developed SG-ML models can be easily shared and/or modified to reproduce or customize for any cyber range. The application of Auto-SGCR is demonstrated through case studies with large-scale substation models. The toolchain along with example SG-ML models have been open-sourced.

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Publication Details

Journal
IEEE Open Journal of the Industrial Electronics Society
Published
2025-01-01
DOI
https://doi.org/10.1109/ojies.2025.3604576
Citations
1
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
1.21
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article

Auto-SGCR: Automated Generation of Smart Grid Cyber Range Using IEC 61850 Standard Models

David M. Nicol, S. M. Suhail Hussain, Daisuke Mashima, Muhammad M. Roomi et al.
1 citations
IEEE Open Journal of the Industrial Electronics Society
Smart Grid Security and Resilience
1.21
article

Auto-SGCR: Automated Generation of Smart Grid Cyber Range Using IEC 61850 Standard Models

David M. Nicol, S. M. Suhail Hussain, Daisuke Mashima, Muhammad M. Roomi, Ee‐Chien Chang
article en
1 citations

Abstract

Digitalization of power grids have made them increasingly susceptible to cyber-attacks in the past decade. Iterative cybersecurity testing (i.e., red-team testing or penetration testing) is indispensable to counter emerging attack vectors and to ensure dependability of critical infrastructure. Furthermore, these can be used to evaluate cybersecurity configuration, effectiveness of the cybersecurity measures against various attack vectors, and to train smart grid cybersecurity experts defending the system. Facilitating extensive experiments narrows the gap between academic research and production environment. A high-fidelity cyber range (a virtual cybersecurity testbed emulating smart grid systems) is vital as it is often infeasible to conduct such experiments and training using production environment. However, the design and implementation of cyber range requires extensive domain knowledge of physical and cyber aspect of the infrastructure. Furthermore, costs incurred for setup and maintenance of cyber range are significant. Moreover, most existing smart grid cyber ranges are designed as a one-off, proprietary system, and are limited in terms of configurability, accessibility, portability, and reproducibility. To address these challenges, an automated Smart grid Cyber Range generation framework (Auto-SGCR) is presented in this paper. Initially a human-/machine-friendly, XML-based modeling language called Smart Grid Modeling Language (SG-ML) was defined, which incorporates IEC 61850 System Configuration Language (SCL) files. Subsequently, a toolchain to parse SG-ML model files and automatically instantiate a functional smart grid cyber range was developed. The developed SG-ML models can be easily shared and/or modified to reproduce or customize for any cyber range. The application of Auto-SGCR is demonstrated through case studies with large-scale substation models. The toolchain along with example SG-ML models have been open-sourced.

IEEE Open Journal of the Industrial Electronics SocietyVol. 6
King Fahd University of Petroleum and Minerals (SA), Singapore University of Technology and Design (SG), University of Illinois Urbana-Champaign (US), National University of Singapore (SG), Advanced Digital Sciences Center (SG)
Openalex Percentile: Top 17%
Smart Grid Security and Resilience
1.21
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