A Blockchain-Based Privacy Information Security Sharing Scheme in Industrial Internet of Things
Open accessAbstract
Due to the competitive relationship among different smart factories, equipment manufacturers cannot integrate the private information of all smart factories to train the intelligent manufacturing equipment fault prediction model and improve the accuracy of intelligent manufacturing equipment fault detection. The use of a low fault recognition rate model for smart factories will cause additional losses for them. In this work, we propose a blockchain-based privacy information security sharing scheme in Industrial Internet of Things (IIoT) to solve the sharing problem of private information in smart factories. Firstly, we abstract smart factories as edge nodes and build decentralized, distributed trusted blockchain networks based on Ethereum clients on simulated edge devices and propose an Intelligent Elliptic Curve Digital Signature Algorithm (IECDSA) to guarantee the ownership of shared information by edge nodes. Secondly, we propose the Reputation-based Delegated Proof of Stake (RDPoS) consensus algorithm to improve the security and reliability of the Delegated Proof of Stake (DPoS) consensus algorithm. Furthermore, we design and implement an incentive mechanism based on information attributes to increase the motivation of edge nodes to share information. Finally, the proposed solution is simulated. Through theoretical and simulation experiments, it is proved that the blockchain-based privacy information security sharing scheme in IIoT can improve the enthusiasm of edge nodes to share information on the premise of ensuring the security of information sharing.
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ECC ensures data security in the IIoT ecosystem.
“ECC ensures data security in the IIoT ecosystem [169].”
From A Critical Overview of Industrial Internet of Things Security and Privacy Issues Using a Layer-Based Hacking Scenario (2023) · cites this paper as [169]
Section 4.1 says the paper’s elliptic-curve signature algorithm (IECDSA) verifies signatures and protects ownership of shared information. The Conclusions also credit the blockchain consensus algorithm with data-consistency security. Thus, the paper supports a narrower security role for an elliptic-curve algorithm, not the claim that ECC alone ensures data security across the IIoT ecosystem. (LLM, conf=0.86)
Experimental — accuracy not yet measuredTraditional blockchain based on Public Key Random Generation (PKRG), which uses secret keys and random nonces to generate new public keys, ensures user anonymity and untraceability in IIoT systems.
“Traditional Blockchain based on Public Key Random Generation (PKRG), which uses secret keys and random nonces to generate randomly new public keys, can indeed ensure user anonymity and untraceability in IIoT systems [169].”
From A Critical Overview of Industrial Internet of Things Security and Privacy Issues Using a Layer-Based Hacking Scenario (2023) · cites this paper as [169]
Section 4.1 (Methods; page unavailable) describes a private key and a pseudo-random number used in the paper’s signature algorithm, but does not describe Public Key Random Generation (PKRG). The supplied passages and searches for PKRG, anonymity, and untraceability found no statement that PKRG ensures either property in IIoT systems. (LLM, conf=0.77)
Experimental — accuracy not yet measured
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Percentages, sums and reported differences re-computed from the paper’s own numbers.
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Cites
Bitcoin: A Peer-to-Peer Electronic Cash SystemPreprint
Nakamoto, S. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3440802 · Cited by 14,600 · see citing works
Bitcoin: A Peer-to-Peer Electronic Cash SystemPreprint
Squarepants, S. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.3977007 · Cited by 11,146 · see citing works
Edge computing: Vision and challenges
Shi, W., Cao, J., Zhang, Q., Li, Y., & Xu, L. (2016) · IEEE Internet of Things Journal · doi:10.1109/jiot.2016.2579198 · Cited by 8,733 · see citing works
Practical Byzantine fault tolerance
Castro, M., & Liskov, B. H. (1999) · Operating Systems Design and Implementation · doi:10.5555/296806.296824 · Cited by 4,026 · see citing works
Koroniotis, N., Moustafa, N., Sitnikova, E., & Turnbull, B. (2019) · Future Generation Computer Systems · doi:10.1016/j.future.2019.05.041 · Cited by 1,983 · see citing works
A Survey of Distributed Consensus Protocols for Blockchain Networks
Xiao, Y., Zhang, N., Lou, W., & Hou, Y. T. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.2969706 · Cited by 1,001 · see citing works
PPCoin: Peer-to-Peer Crypto-Currency with Proof-of-Stake
King, S., & Nadal, S. (2012) · Cited by 984 · see citing works
Kang, J., Xiong, Z., Niyato, D. T., Xie, S., & Zhang, J. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2940820 · Cited by 961 · see citing works
Blockchain Empowered Asynchronous Federated Learning for Secure Data Sharing in Internet of Vehicles
Lu, Y., Huang, X., Zhang, K., Maharjan, S., & Zhang, Y. (2020) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2020.2973651 · Cited by 733 · see citing works
Self-citationA Survey on Machine Learning for Data Fusion
Meng, T., Jing, X., Yan, Z., & Pedrycz, W. (2020) · Information Fusion · doi:10.1016/j.inffus.2019.12.001 · Cited by 677 · see citing works
A Learning-Based Incentive Mechanism for Federated Learning
Zhan, Y., Li, P., Qu, Z., Zeng, D., & Guo, S. (2020) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.2967772 · Cited by 602 · see citing works
Edge Computing Security: State of the Art and Challenges
Xiao, Y., Jia, Y., Liu, C., Cheng, X., Yu, J., & Lv, W. (2019) · Proceedings of the IEEE · doi:10.1109/jproc.2019.2918437 · Cited by 543 · see citing works
Privacy-Preserved Data Sharing Towards Multiple Parties in Industrial IoTs
Zheng, X., & Cai, Z. (2020) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2020.2980802 · Cited by 461 · see citing works
Torky, M. F., & Hassanein, A. E. (2020) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2020.105476 · Cited by 409 · see citing works
Blockchain-based authentication and authorization for smart city applications
Esposito, C., Ficco, M., & Gupta, B. B. (2020) · Information Processing & Management · doi:10.1016/j.ipm.2020.102468 · Cited by 399 · see citing works
Assessing Blockchain Consensus and Security Mechanisms against the 51% Attack
Sayeed, S., & Marco-Gisbert, H. (2019) · Applied Sciences · doi:10.3390/app9091788 · Cited by 380 · see citing works
Jiang, D. (2019) · Computer Communications · doi:10.1016/j.comcom.2019.10.035 · Cited by 236 · see citing works
Tezuka, S. (1995) · Springer eBooks · doi:10.1007/978-1-4615-2317-8 · Cited by 197 · see citing works
Liu, L., Feng, J., Pei, Q., Chen, C., Ming, Y., Shang, B., & Dong, M. (2020) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.3048345 · Cited by 189 · see citing works
A blockchain-based scheme for privacy-preserving and secure sharing of medical data
Huang, H., Zhu, P., Xiao, F., Sun, X., & Huang, Q. (2020) · Computers & Security · doi:10.1016/j.cose.2020.102010 · Cited by 188 · see citing works
Incentive Mechanism of Data Storage Based on Blockchain for Wireless Sensor Networks
Ren, Y., Liu, Y., Ji, S., Sangaiah, A. K., & Wang, J. (2018) · Mobile Information Systems · doi:10.1155/2018/6874158 · Cited by 153 · see citing works
A survey on technologies and security protocols: Reference for future generation IoT
Yugha, R., & Chithra, S. (2020) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2020.102763 · Cited by 147 · see citing works
A Cloud Edge Collaborative Intelligence Method of Insulator String Defect Detection for Power IIoT
Song, C., Xu, W., Han, G., Zeng, P., Wang, Z., & Yu, S. (2020) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.3039226 · Cited by 83 · see citing works
Zhang, W., Yang, D., Xu, Y., Huang, X., Zhang, J., & Gidlund, M. (2020) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2020.3029551 · Cited by 80 · see citing works
A New Election Algorithm for DPos Consensus Mechanism in Blockchain
Luo, Y., Chen, Y., Chen, Q., & Liang, Q. (2018) · International Conference on Digital Home (ICDH) · doi:10.1109/icdh.2018.00029 · Cited by 73 · see citing works
Incentive Mechanism for Edge-Computing-Based Blockchain
Chang, Z., Guo, W., Guo, X., Zhou, Z., & Ristaniemi, T. (2020) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2020.2973248 · Cited by 67 · see citing works
Security information transmission algorithms for IoT based on cloud computing
Ding, L., Wang, Z., Wang, X., & Wu, D. (2020) · Computer Communications · doi:10.1016/j.comcom.2020.03.010 · Cited by 57 · see citing works
A Peer to Peer Money Transfer Using SHA256 and Merkle Tree
Dhumwad, S., Sukhadeve, M., Naik, C., Manjunath, K. N., & Prabhu, S. (2017) · doi:10.1109/adcom.2017.00013 · Cited by 35 · see citing works
DPoSB: Delegated Proof of Stake with node's behavior and Borda Count
Tan, C., & Xiong, L. (2020) · IEEE Information Technology and Mechatronics Engineering Conference (ITOEC) · doi:10.1109/itoec49072.2020.9141744 · Cited by 30 · see citing works
BSV-PAGS: Blockchain-based special vehicles priority access guarantee scheme
Wang, Y., Yu, J.-G., Yan, B., Wang, G.-J., & Shan, Z. (2020) · Computer Communications · doi:10.1016/j.comcom.2020.07.012 · Cited by 27 · see citing works
Self-citationNichols, K. M. (2021) · ACM Conference on Information-Centric Networking (ICN) · doi:10.1145/3460417.3482972 · Cited by 20 · see citing works
Improvement of DPoS Consensus Based on Block Chain
Zhang, W., & Yunsheng, G. (2019) · doi:10.1145/3378065.3378132 · Cited by 5 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
A Blockchain-Enabled Secure Digital Twin Framework for Early Botnet Detection in IIoT Environment
Salim, M. M., Alowonou, K. C., Nurbek, T., Park, H., & Park, J. H. (2022) · Sensors · doi:10.3390/s22166133 · Cited by 46 · see citing works
Eyeleko, A. H., & Feng, T. (2023) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3308195 · Cited by 38 · see citing works
“Wang et al. [169] proposed a blockchain-based privacy-sharing scheme in IIoT to protect keys, ensure data consistency, and incentivize communication.”
BackgroundThe Evolution and Optimization Strategies of a PBFT Consensus Algorithm for Consortium Blockchains
Yuan, F., Huang, X., Zheng, L., Wang, L., Wang, Y., Yan, X., Gu, S., & Peng, Y. (2025) · Information · doi:10.3390/info16040268 · Cited by 36 · see citing works
Self-citationOpen Logistics: Blockchain-Enabled Trusted Hyperconnected Logistics Platform
Barenji, A. V., & Montreuil, B. (2022) · Sensors · doi:10.3390/s22134699 · Cited by 24 · see citing works
Who should own the data? The impact of data value creation on data ownership
Zheng, C., Li, Y., & Dou, R. (2024) · Computers & industrial engineering · doi:10.1016/j.cie.2024.110093 · Cited by 13 · see citing works
Sohail, M. N., Anjum, A., Saeed, I. A., Syed, M. H., Jantsch, A., & Rehman, S. (2024) · IEEE Access · doi:10.1109/access.2024.3382571 · Cited by 8 · see citing works
A survey on blockchain-based privacy preserving techniques for edge internet of things
Ranjan, A. K., & Kumar, P. (2025) · International Journal of Computers and Applications · doi:10.1080/1206212x.2025.2498687 · Cited by 8 · see citing works
Tong, W., Yang, L., Li, Z., Jin, X., & Tan, L. (2024) · Sensors · doi:10.3390/s24031035 · Cited by 9 · see citing works
Taluja, A., R, H. K. G., Thangarasu, J., & Pingle, Y. P. (2025) · Evolving Systems · doi:10.1007/s12530-025-09719-4 · Cited by 6 · see citing works
Wang, Y., Zhang, K., Zhao, X., & Hu, X. (2023) · Internet of Things · doi:10.1016/j.iot.2023.101026 · Cited by 6 · see citing works
Self-citationAdvanced Approaches for Emerging Networks: Location Verification and Block-Based Resource Allocation
Ramkumar, G., Giri, J. P., & Sabri, M. O. (2025) · International Conference on Integrated Circuits and Communication Systems (ICICACS) · doi:10.1109/icicacs65178.2025.10968379 · Cited by 5 · see citing works
Intellig_block: enhancing IoT security with blockchain-based adversarial machine learning protection
(2023) · International Journal of Advanced Technology and Engineering Exploration · doi:10.19101/ijatee.2023.10101465 · Cited by 3 · see citing works
Navaz, A. N., Kassabi, H. T. E., Serhani, M. A., & Barka, E. S. (2023) · Applied Sciences · doi:10.3390/app132413114 · Cited by 2 · see citing works
Wang, L., Guo, X., Zhang, X., & Gang, Z. (2022) · Journal of Sensors · doi:10.1155/2022/1263330 · Cited by 2 · see citing works
RetractedData Security Transmission and Privacy Protection Scheme for Industrial Internet of Things
Tong, W., Yang, L., Li, Z., Zhao, J., Pan, F., & Tan, L. (2024) · International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE) · doi:10.1109/iccsie61360.2024.10698294 · Cited by 1 · see citing works
Erman, K. N., & Çınar, A. C. (2025) · Multimedia Tools and Applications · doi:10.1007/s11042-025-21122-4 · Cited by 1 · see citing works
Wang, C., Dai, C., Pu, X., & Wang, R. (2023) · International Conference on Information Economy, Data Modeling and Cloud Computing (ICIDC) · doi:10.4108/eai.2-6-2023.2334627
Privacy-Preserving Analysis of Blockchain Based Federated Learning Method in IIoT
Sindi, A. O. N., Si, P., Li, Q., Yan, S., & Liu, J. (2025) · Communications in computer and information science · doi:10.1007/978-981-96-6462-7_2
Aldarwish, A. J. Y., Patel, K., Yaseen, A. A., & Yassin, A. A. (2025) · Lecture notes in electrical engineering · doi:10.1007/978-981-96-6034-6_38
An enhanced data sharing security over blockchain using montgomery curve-based multikey scheme
Mathur, N., Sinha, S., Tyagi, R. K., & Jatana, N. (2026) · Engineering Research Express · doi:10.1088/2631-8695/ae2f23
- Authors
- Wang, Y., Che, T., Zhao, X., Zhou, T., Zhang, K., & Hu, X.
- Affiliations
- China University of Mining and Technology (CN)
- Chengdu Neusoft University (CN)
- Corresponding author
- Zhao, Xiaohu
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2022-04-30
- Volume
- 22
- Issue
- 9
- Pages
- 3426
- ISSN
- 1424-8220 (ISSN-L)
- PMC
- PMC9103928
- OpenAlex
- W4225285241
- Cited by
- 20
- References
- 32
- Citations by year
- 2026: 1 · 2025: 7 · 2024: 4 · 2023: 5 · 2022: 3
- FWCI
- 4.70
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sensors (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Fundamental Research Funds (2020ZDPY0223)
- Topics
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Keywords
- blockchain, Industrial Internet of Things, smart factory, equipment failure prediction, fault detection, ECDSA, Ethereum, delegated proof of stake, reputation-based consensus, incentive mechanisms, edge nodes, data ownership
- MeSH terms
- Internet of Things, Blockchain, Humans, Reproducibility of Results, Computer Security, Privacy, Information Dissemination
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