Enhancing IIoT Security Using Digital Twins in Industry 5.0: A Systematic Literature Review Md Whaiduzzaman , Natasha Tanzila Monalisa , Shinthi Tasnim Himi , Shirin Sultana , Tony Jan , Alistair Barros Business and Hospitality Centre for Artificial Intelligence Research and Optimisation (AIRO) Design and Creative Technology Research and Innovation Office Research output : Contribution to journal › Review article › peer-review Abstract The rapid advancement of Industry 5.0 and the concurrent growth of the Industrial Internet of Things (IIoT) present significant cybersecurity challenges necessitating advanced solutions. Digital Twin technology, which enables the creation of near-perfect digital replicas of physical systems, offers a promising approach to enhancing security and safety. This paper presents a literature review of the existing research to identify the challenges and future directions for integrating DT technology into IIoT from a security perspective. We aim to establish a comprehensive understanding of emerging features, including predictive analytics, real-time threat detection, and cybersecurity management. Additionally, this review highlights critical gaps, including complexity, model fidelity, real-time data processing, and scalability, which hinder the successful deployment of DT technology. Our study will assist researchers, cybersecurity practitioners, and policymakers in understanding the potential, limitations, and future advancements of this crucial area. Original language English Article number 209 Journal Information (Switzerland) Volume 17 Issue number 2 DOIs https://doi.org/10.3390/info17020209 Publication status Published - Feb 2026 UN SDGs This output contributes to the following UN Sustainable Development Goals (SDGs) SDG 9 Industry, Innovation, and Infrastructure Keywords anomaly detection cybersecurity cyber–physical systems digital twin industrial internet of things (IIoT) Industry 5.0 intrusion detection smart industry zero-trust architecture Access to Document 10.3390/info17020209 Other files and links Link to publication in Scopus Fingerprint Dive into the research topics of 'Enhancing IIoT Security Using Digital Twins in Industry 5.0: A Systematic Literature Review'. Together they form a unique fingerprint. Systematic Literature Review Keyphrases 100% Industry 5.0 Keyphrases 100% Industrial Internet of Things (IIoT) Keyphrases 100% Digital Twin in Industry Keyphrases 100% DT Technologies Keyphrases 100% Industrial Internet of Things Security Keyphrases 100% Cybersecurity Computer Science 100% Industrial Internet of Things Computer Science 100% View full fingerprint Cite this APA Author BIBTEX Harvard Standard RIS Vancouver Whaiduzzaman, M. , Monalisa, N. T., Himi, S. T., Sultana, S. , Jan, T. , & Barros, A. (2026). Enhancing IIoT Security Using Digital Twins in Industry 5.0: A Systematic Literature Review . Information (Switzerland) , 17 (2), Article 209. https://doi.org/10.3390/info17020209 Whaiduzzaman, Md ; Monalisa, Natasha Tanzila ; Himi, Shinthi Tasnim et al. / Enhancing IIoT Security Using Digital Twins in Industry 5.0 : A Systematic Literature Review . In: Information (Switzerland) . 2026 ; Vol. 17, No. 2. @article{2cf757e774bb4db08245cb0f53a251e3, title = "Enhancing IIoT Security Using Digital Twins in Industry 5.0: A Systematic Literature Review", abstract = "The rapid advancement of Industry 5.0 and the concurrent growth of the Industrial Internet of Things (IIoT) present significant cybersecurity challenges necessitating advanced solutions. Digital Twin technology, which enables the creation of near-perfect digital replicas of physical systems, offers a promising approach to enhancing security and safety. This paper presents a literature review of the existing research to identify the challenges and future directions for integrating DT technology into IIoT from a security perspective. We aim to establish a comprehensive understanding of emerging features, including predictive analytics, real-time threat detection, and cybersecurity management. Additionally, this review highlights critical gaps, including complexity, model fidelity, real-time data processing, and scalability, which hinder the successful deployment of DT technology. Our study will assist researchers, cybersecurity practitioners, and policymakers in understanding the potential, limitations, and future advancements of this crucial area.", keywords = "anomaly detection, cybersecurity, cyber–physical systems, digital twin, industrial internet of things (IIoT), Industry 5.0, intrusion detection, smart industry, zero-trust architecture", author = "Md Whaiduzzaman and Monalisa, \{Natasha Tanzila\} and Himi, \{Shinthi Tasnim\} and Shirin Sultana and Tony Jan and Alistair Barros", note = "Publisher Copyright: {\textcopyright} 2026 by the authors.", year = "2026", month = feb, doi = "10.3390/info17020209", language = "English", volume = "17", journal = "Information (Switzerland)", issn = "2078-2489", pub...