Risk auditing for Digital Twins in cyber physical systems: A systematic review
Shahed Otoom
Published: 2025/01/29
Abstract
Digital Twins are emerging as a transformative technology within Cyber-Physical Systems (CPS), offering enhanced optimization, predictive maintenance, and real-time monitoring. However, their integration also introduces significant security challenges. These include vulnerabilities such as data breaches, unauthorized access, and cyber-attacks that disrupt real-time data flow between their physical and digital components. The involvement of IoT devices, sensors, and complex networked environments expands the attack surface, making Digital Twins susceptible to threats like Distributed Denial-ofService (DDoS) attacks, malware infiltration, and insider sabotage. Effective risk management and assessment are crucial in identifying vulnerabilities, evaluating risks, and implementing mitigation strategies. Securing Digital Twins ensures data integrity, system reliability, and the continued functionality of the physical assets they represent. This paper aims to classify the various security threats associated with Digital Twins and propose structured risk management approaches to enhance their security within CPS. By addressing these challenges, organizations can ensure the dependability and trustworthiness of Digital Twin implementations across industries such as manufacturing, healthcare, smart cities, and IoT ecosystems.
Keywords
How to Cite the Article
Otoom, S. (2025). Risk auditing for Digital Twins in cyber physical systems: A systematic review. Journal of Cyber Security and Risk Auditing, 2025(1), 22–35. https://doi.org/10.63180/jcsra.thestap.2025.1.3
Risk auditing for Digital Twins in cyber physical systems: A systematic review is licensed under CC BY 4.0
References
- Alcaraz, C., & Lopez, J. (2022). Digital twin: A comprehensive survey of security threats. IEEE Communications Surveys & Tutorials, 24(3), 1475-1503.
- Suhail, S., Jurdak, R., & Hussain, R. (2022). Security attacks and solutions for digital twins. arXiv preprint arXiv:2202.12501.
- Varghese, S. A., Ghadim, A. D., Balador, A., Alimadadi, Z., & Papadimitratos, P. (2022, March). Digital twin-based intrusion detection for industrial control systems. In 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) (pp. 611-617). IEEE.
- Carr, C., Wang, S., Wang, P., & Han, L. (2022). Attacking digital twins of robotic systems to compromise security and safety. arXiv preprint arXiv:2211.09507.
- Wang, Y., Su, Z., Guo, S., Dai, M., Luan, T. H., & Liu, Y. (2023). A survey on digital twins: Architecture, enabling technologies, security and privacy, and future prospects. IEEE Internet of Things Journal, 10(17), 14965-14987.
- Khan, L. U., Han, Z., Saad, W., Hossain, E., Guizani, M., & Hong, C. S. (2022). Digital twin of wireless systems: Overview, taxonomy, challenges, and opportunities. IEEE Communications Surveys & Tutorials, 24(4), 2230-2254.
- Sarker, I. H., Janicke, H., Mohsin, A., Gill, A., & Maglaras, L. (2024). Explainable AI for cybersecurity automation, intelligence and trustworthiness in digital twin: Methods, taxonomy, challenges and prospects. ICT Express.
- Jeremiah, S. R., El Azzaoui, A., Xiong, N. N., & Park, J. H. (2024). A Comprehensive Survey of Digital Twins: Applications, Technologies and Security Challenges. Journal of Systems Architecture, 103120.
- Psaltikidis, T. (2024). Digital twins security, privacy and safety: threats, risks and measures.
- Sifat, M. M. H., Choudhury, S. M., Das, S. K., Ahamed, M. H., Muyeen, S. M., Hasan, M. M., ... & Das, P. (2023). Towards electric digital twin grid: Technology and framework review. Energy and AI, 11, 100213.