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

Alexandre Rekeraho (), Daniel Tudor Cotfas, Titus C. Balan, Petru Adrian Cotfas, Rebecca Acheampong and Emmanuel Tuyishime
Additional contact information
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

Sustainability, 2025, vol. 17, issue 6, 1-31

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.

Keywords: cybersecurity; IoT security; sustainable energy; energy resilience; threat model; STRIDE; solar energy; renewable energy; smart solar energy; DREAD (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/17/6/2386/pdf (application/pdf)
https://www.mdpi.com/2071-1050/17/6/2386/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:6:p:2386-:d:1608368

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().