Abstract

This paper focuses on building a secure Digital Twin (DT) system that can work safely in a cloud environment. A Digital Twin is basically a virtual version of a real physical device, and it helps in monitoring, analyzing, and running simulations. DTs are becoming important in many areas like manufacturing, hospitals, and even self-driving vehicles. But when real-time data is sent to the cloud there is always a risk that someone unauthorized might access it or modify it. This creates serious privacy and security issues. To solve this, we designed a blockchain-based security method that uses three factors to authenticate users. The idea is to make sure only the right person can access the system and that the data being transferred stays private and unaltered. The method is lightweight, meaning it does not require too much storage or processing power. We also tested the security of the system using different formal and informal techniques. The results showed that it can defend against common attacks like impersonation and offline password guessing, which many existing protocols still fail to handle properly. Overall, the paper shows that it is possible to build a secure and scalable DT framework for cloud-assisted systems. By protecting the data exchanged between devices and the cloud, this approach supports the growing use of Digital Twins and helps create safer and more privacy-focused IoT environments.

References

• S. Nakamoto, “Bitcoin: A peer-to-peer electronic cash system,” 2008. [Online]. Available: https://bitcoin.org/bitcoin.pdf
• L. Da Xu, W. He, and S. Li, “Internet of Things in industries: A survey,” IEEE Transactions on Industrial Informatics, vol. 10, no. 4, pp. 2233–2243, 2014.
• K. Christidis and M. Devetsikiotis, “Blockchains and smart contracts for the Internet of Things,” IEEE Access, vol. 4, pp. 2292–2303, 2016.
• A. Dorri, S. S. Kanhere, and R. Jurdak, “Blockchain in Internet of Things: Challenges and solutions,” in Proc. IEEE Intl. Conf. on Pervasive Computing and Communications Workshops (PerCom Workshops), 2017, pp. 529–534.
• A. A. Salahuddin, A. Al-Fuqaha, and M. Guizani, “Software-defined networking for next-generation Internet of Things: A survey,” IEEE Communications Magazine, vol. 55, no. 9, pp. 72–79, 2017.
• Q. Xia, E. B. Sifah, A. Smahi, S. Amofa, and X. Zhang, “BBDS: Blockchain-based data sharing for electronic medical records in cloud environments,” Information, vol. 8, no. 2, pp. 44–59, 2017.
• S. Rathore, P. K. Sharma, and J. H. Park, “Social network security: Issues, challenges, threats, and solutions,” Information Sciences, vol. 421, pp. 43–69, 2017.
• P. Zhang, J. White, D. C. Schmidt, G. Lenz, and S. T. Rosenbloom, “FHIRChain: Applying blockchain to securely and scalably share clinical data,” Computational and Structural Biotechnology Journal, vol. 16, pp. 267–278, 2018.
• H. Kim and M. Laskowski, “Towards an ontology-driven blockchain design for supply-chain provenance,” Intelligent Systems in Accounting, Finance and Management, vol. 25, no. 1, pp. 18–27, 2018.
• Y. Ren, Y. Zhu, and J. Wu, “Privacy-preserving data aggregation for big data in cloud computing,” IEEE Transac-tions on Cloud Computing, vol. 6, no. 1, pp. 68–78, 2018.
• R. Zhang and L. Xie, “Security and privacy in smart health: Efficient policy-hiding attribute-based access control,”
• C. Esposito, A. De Santis, G. Tortora, H. Chang, and K.R. Choo, “Blockchain: A panacea for healthcare cloud-based data security and privacy?,” IEEE Cloud Computing, vol. 5, no. 1, pp. 31–37, 2018.
• X. Xu, Q. Lu, Y. Liu, L. Zhu, H. Yao, and A. V.Vasilakos, “Designing blockchain-based applications: A case study for imported product traceability,” Future Generation Computer Systems, vol. 92, pp. 399–406, 2019.
• F. Tao, H. Zhang, A. Liu, and A. Y. Nee, “Digital twin in industry: State-of-the-art,” IEEE Transactions on Industrial Informatics, vol. 15, no. 4, pp. 2405–2415, 2019.
• A. Fuller, Z. Fan, C. Day, and C. Barlow, “Digital twin: Enabling technologies, challenges and open research,” IEEE Access, vol. 8, pp. 108952–108971, 2020.
• Y. Lu, C. Liu, I. Kevin, and T. Xu, “Digital twin-driven smart manufacturing: Connotation, reference model, applications and research issues,” Robotics and Computer-Integrated Manufacturing, vol. 61, p. 101837, 2020.
• X. Zheng, Z. Zheng, X. Chen, and X. Luo, “Blockchain-based trusted data sharing among trusted stake-holders in industrial IoT,” IEEE Transactions on Industrial Informatics, vol. 16, no. 9, pp. 6132–6142, 2020.
• A. K. Tyagi, R. Kumar, and M. S. Obaidat, “Blockchain security: Analysis of consensus protocol and applications,” IEEE Access, vol. 9, pp. 12554–12565, 2021.
• R. Belchior, A. Vasconcelos, S. Guerreiro, and M. Cor-reia, “A survey on blockchain interoperability: Past, present, and future trends,” ACM Computing Surveys, vol. 54, no. 8, pp. 1–41, 2021.
• J. Zhang, F. Tao, and C. Liu, “Blockchain-based digital twin sharing in cloud manufacturing,” IEEE Transactions on Industrial Informatics, vol. 17, no. 6, pp.2025.