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Cybersecurity Threat Modeling for IoT-Integrated Smart Solar Energy Systems: Strengthening Resilience for Global Energy Sustainability

Author

Listed:
  • Alexandre Rekeraho

    (Electronics and Computers Department, Transilvania University of Brasov, 500036 Brasov, Romania)

  • Daniel Tudor Cotfas

    (Electronics and Computers Department, Transilvania University of Brasov, 500036 Brasov, Romania)

  • Titus C. Balan

    (Electronics and Computers Department, Transilvania University of Brasov, 500036 Brasov, Romania)

  • Petru Adrian Cotfas

    (Electronics and Computers Department, Transilvania University of Brasov, 500036 Brasov, Romania)

  • Rebecca Acheampong

    (Electronics and Computers Department, Transilvania University of Brasov, 500036 Brasov, Romania)

  • Emmanuel Tuyishime

    (Electronics and Computers Department, Transilvania University of Brasov, 500036 Brasov, Romania)

Abstract

The integration of Internet of Things (IoT) technologies into solar energy systems has transformed them into smart solar energy systems, enabling advanced real-time monitoring, control, and optimization. However, this connectivity also expands the attack surface, exposing critical components to cybersecurity threats that could compromise system reliability and long-term sustainability. This study presents a comprehensive cybersecurity threat modeling analysis for IoT-based smart solar energy systems using the STRIDE threat model to systematically identify, categorize, and assess potential security risks. These risks, if unmitigated, could disrupt operations and hinder large-scale adoption of solar energy. The methodology begins with a system use case outlining the architecture and key components, including sensors, PV modules, IoT nodes, gateways, cloud infrastructure, and remote-access interfaces. A Data Flow Diagram (DFD) was developed to visualize the data flow and identify the critical trust boundaries. The STRIDE model was applied to classify threats, such as spoofing, tampering, repudiation, information disclosure, denial of service, and elevation of privilege across components and their interactions. The DREAD risk assessment model was then used to prioritize threats based on the Damage Potential, Reproducibility, Exploitability, Affected Users, and Disability. The results indicate that most threats fall into the high-risk category, with scores ranging from 2.6 to 2.8, emphasizing the need for targeted mitigation. This study proposes security recommendations to address the identified threats and enhance the resilience of IoT-enabled solar energy systems. By securing these infrastructures, this research supports the transition to sustainable energy by ensuring system integrity and protection against cyber threats. The combined use of STRIDE and DREAD provides a robust framework for identifying, categorizing, and prioritizing risks, enabling effective resource allocation and targeted security measures. These findings offer critical insights into safeguarding renewable energy systems against evolving cyber threats, contributing to global energy sustainability goals in an increasingly interconnected world.

Suggested Citation

  • Alexandre Rekeraho & Daniel Tudor Cotfas & Titus C. Balan & Petru Adrian Cotfas & Rebecca Acheampong & Emmanuel Tuyishime, 2025. "Cybersecurity Threat Modeling for IoT-Integrated Smart Solar Energy Systems: Strengthening Resilience for Global Energy Sustainability," Sustainability, MDPI, vol. 17(6), pages 1-31, March.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:6:p:2386-:d:1608368
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    References listed on IDEAS

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    1. Zhai, Xiangyu & Li, Zening & Li, Zhengmao & Xue, Yixun & Chang, Xinyue & Su, Jia & Jin, Xiaolong & Wang, Peng & Sun, Hongbin, 2025. "Risk-averse energy management for integrated electricity and heat systems considering building heating vertical imbalance: An asynchronous decentralized approach," Applied Energy, Elsevier, vol. 383(C).
    2. Ebrahim Mohammadi & Gerry Moschopoulos & Aoxia Chen, 2025. "Boosting Solar Sustainability: Performance Assessment of Roof-Mounted PV Arrays Under Snow Considering Various Module Interconnection Schemes," Sustainability, MDPI, vol. 17(1), pages 1-28, January.
    3. Dalibor Dobrilovic & Jasmina Pekez & Eleonora Desnica & Ljiljana Radovanovic & Ivan Palinkas & Milica Mazalica & Luka Djordjević & Sinisa Mihajlovic, 2023. "Data Acquisition for Estimating Energy-Efficient Solar-Powered Sensor Node Performance for Usage in Industrial IoT," Sustainability, MDPI, vol. 15(9), pages 1-22, April.
    4. Yunus Kareem & Djamel Djenouri & Essam Ghadafi, 2024. "A Survey on Emerging Blockchain Technology Platforms for Securing the Internet of Things," Future Internet, MDPI, vol. 16(8), pages 1-19, August.
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