Issue |
EPJ Web Conf.
Volume 330, 2025
The 5th International Conference on Electrical Sciences and Technologies in the Maghreb (CISTEM 2024)
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Article Number | 03010 | |
Number of page(s) | 8 | |
Section | Power Systems, Renewable Energy Systems, and Smart Grids | |
DOI | https://doi.org/10.1051/epjconf/202533003010 | |
Published online | 30 June 2025 |
https://doi.org/10.1051/epjconf/202533003010
Threat Analysis of Power System Case Study via STRIDE Threat Model in Digital Twin Real-time Platform
1 Mechatronics Engineering Department, German Jordanian University, Amman, Jordan.
2 Smart Grid LAB, German Jordanian University, Amman, Jordan.
3 Faculty of Engineering and Environment, Northumbria University, Newcastle, United Kingdom.
4 School of Engineering and Computer Science, Oakland University, Michigan, USA.
* Corresponding author: hani.mohsen@gju.edu.jo
Published online: 30 June 2025
Threat modeling is a pivotal analytical procedure employed to specify the potential threats and select the appropriate security measures. It helps reduce the risk of cyber-attacks that may target several components of the cyber-physical power systems. Accordingly, identifying potential cyber threats and assessing their consequences is an imperative aspect of the supervision and monitoring of power systems. This paper presents a threat analysis scheme of a power system case study utilizing the STRIDE threat model methodology. The developed model addresses several attack and threat scenarios combined into an attack graph model. In terms of security measures, this paper introduces a Secure, Encrypted, Authenticated Communication Channel (SEAC2), which is a two-level encryption method to secure the communication layer. Further, this study introduces an open-source Digital Twin (DT) platform that enables a real-time comprehensive assessment of the system's energy dynamics. It also prioritizes threat detection as another crucial aspect. A real case study from the Jordanian electrical network has been utilized in this study to validate the proposed platform.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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