A Blockchain-Based Cross-Domain Data Transmission Scheme for Industrial Internet of Things With Edge-Cloud Computing
The rapid evolution of the Industrial Internet of Things (IIoT) and widespread adoption of smart devices have profoundly reshaped traditional industrial production and management. Facilitated cross-domain data transmission between these devices has greatly boosted intelligence and efficiency in IIoT. Yet despite progress in cross-domain transmission, existing schemes still face severe challenges: complex hierarchical architectures, cross-domain trust issues, and high computational costs. To tackle these problems, we propose a blockchain based cross-domain data transmission scheme for IIoT, integrated with edge-cloud computing. First, we enhance crossdomain transmission in edge-cloud environments by developing a lightweight blockchain-assisted framework, which cuts down redundant entity interactions. Second, we address inter-domain trust in IIoT by establishing trust relationships and computing relationship keys. Finally, we introduce a lightweight blockchain based authentication and key agreement protocol to simplify cross-domain data transmission between smart devices. Security analysis shows the proposed scheme achieves strong security in the real-or-random model, effectively resisting various potential threats. Performance analysis and blockchain simulations further confirm its practical applicability for IIoT deployment
Authors
- Xiaofeng Chen (ORCID: https://orcid.org/0000-0001-5858-5070)
- Qingfeng Cheng (ORCID: https://orcid.org/0000-0001-6149-4807)
- Xingxing Chen (ORCID: https://orcid.org/0009-0005-9842-8973)
- Xiangyang Luo (ORCID: https://orcid.org/0000-0003-3225-4649)
Institutions
- Xidian University (CN)
- PLA Information Engineering University (CN)
Publication Details
- Journal
- IEEE Transactions on Services Computing
- Published
- 2025-08-26
- DOI
- https://doi.org/10.1109/tsc.2025.3603155
- Citations
- 2
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 1.68