Blockchain-based lightweight trusted data interaction scheme for cross-domain IIoT^✩

Abstract

To facilitate cross-domain data interaction in the Industrial Internet of Things (IIoT), establishing trust between multiple administrative domains is essential. Although blockchain technology has been proposed as a solution, current techniques still suffer from issues related to efficiency, security, and privacy. Our research aims to address these challenges by proposing a lightweight, trusted data interaction scheme based on blockchain, which reduces redundant interactions among entities. We enhance the traditional Practical Byzantine Fault Tolerance (PBFT) algorithm to support lightweight distributed consensus in large-scale IIoT scenarios. Introducing a composite digital signature algorithm and incorporating veto power minimizes resource consumption and eliminates ineffective consensus operations. The experimental results show that, compared with PBFT, our scheme reduces latency by 27.2%, thereby improving communication efficiency and resource utilization. Furthermore, we develop a lightweight authentication technique specifically for cross-domain IIoT, leveraging blockchain technology to achieve distributed collaborative authentication. The performance comparisons indicate that our method significantly outperforms traditional schemes, with an average authentication latency of approximately 151 milliseconds. Additionally, we introduce a trusted federated learning (FL) algorithm that ensures comprehensive trust assessments for devices across different domains while protecting data privacy. Extensive simulations and experiments validate the reliability of our approach.

Keywords

Blockchain / Industrial internet of things / Federated learning / Cross-domain / Authentication

References

[1] J. Aas, R. Barnes, B. Case, Z. Durumeric, P. Eckersley, A. Flores-López, J.A. Hal-derman, J. Hoffman-Andrews, J. Kasten, E. Rescorla, et al., Let’s encrypt: an au-tomated certificate authority to encrypt the entire web,in: Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, 2019, pp. 2473-2487.

[2] H. Lasi, P. Fettke, H.-G. Kemper, T. Feld, M. Hoffmann, Industry 4.0, Bus. Inf. Syst. Eng. 6 (2014) 239-242.

[3] C. Li, H. Yang, Z. Sun, Q. Yao, B. Bao, J. Zhang, A.V. Vasilakos, Federated hierarchical trust-based interaction scheme for cross-domain industrial IoT, IEEE Internet Things J. 10 (1) (2022) 447-457.

[4] J. Chen, Z. Zhan, K. He, R. Du, D. Wang, F. Liu, Xauth: efficient privacy-preserving cross-domain authentication, IEEE Trans. Dependable Secure Comput. 19 (5) (2021) 3301-3311.

[5] J. Guan, Y. Wu, S. Yao, T. Zhang, X. Su, C. Li, Bsla: blockchain-assisted secure and lightweight authentication for sgin, Comput.commun. 176 (2021) 46-55.

[6] M. Wang, L. Rui, Y. Yang, Z. Gao, X. Chen, A blockchain-based multi-ca cross-domain authentication scheme in decentralized autonomous network, IEEE Trans. Netw. Serv. Manag. 19 (3) (2022) 2664-2676.

[7] C. Feng, B. Liu, Z. Guo, K. Yu, Z. Qin, K.-K.R. Choo, Blockchain-based cross-domain authentication for intelligent 5g-enabled internet of drones, IEEE Internet Things J. 9 (8) (2021) 6224-6238.

[8] L. Wang, Y. Tian, D. Zhang, Toward cross-domain dynamic accumulator authentica-tion based on blockchain in internet of things, IEEE Trans. Ind. Inform. 18 (4) (2021) 2858-2867.

[9] M. Shen, H. Liu, L. Zhu, K. Xu, H. Yu, X. Du, M. Guizani, Blockchain-assisted secure device authentication for cross-domain industrial IoT, IEEE J. Sel. Areas Commun. 38 (5) (2020) 942-954.

[10] J. Wang, K. Han, S. Fan, Y. Zhang, H. Tan, G. Jeon, Y. Pang, J. Lin, A logistic mapping-based encryption scheme for wireless body area networks, Future Gener. Comput. Syst. 110 (2020) 57-67.

[11] Z. Liu, C. Hu, H. Xia, T. Xiang, B. Wang, J. Chen, Spdts: a differential privacy-based blockchain scheme for secure power data trading, IEEE Trans. Netw. Serv. Manag. 19 (4) (2022) 5196-5207.

[12] A. Rahman, M.J. Islam, S.S. Band, G. Muhammad, K. Hasan, P. Tiwari, Towards a blockchain-sdn-based secure architecture for cloud computing in smart industrial IoT, Digit.commun. Netw. 9 (2) (2023) 411-421.

[13] X. Zhang, C. Xu, H. Wang, Y. Zhang, S. Wang, Fs-peks: lattice-based forward secure public-key encryption with keyword search for cloud-assisted industrial internet of things, IEEE Trans. Dependable Secure Comput. 18 (3) (2019) 1019-1032.

[14] J. Zhang, C. Luo, M. Carpenter, G. Min, Federated learning for distributed IIoT in-trusion detection using transfer approaches, IEEE Trans. Ind. Inform. 19 (7) (2023) 8159-8169.

[15] M. Castro, B. Liskov, Practical byzantine fault tolerance and proactive recovery, ACM Trans. Comput. Syst. 20 (4) (2002) 398-461.

[16] R. Singh, S. Nandi, An improved pbft-based consensus protocol for industrial IoT, in: 2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing Workshops (CCGridW), IEEE, 2023, pp. 311-312.

[17] F. Tang, T. Xu, J. Peng, N. Gan, Tp-pbft: a scalable pbft based on threshold proxy signature for IoT-blockchain applications, IEEE Internet Things J. 11 (9) (2024) 15434-15449.

[18] M.S. Hajar, H.K. Kalutarage, M.O. Al-Kadri, Security challenges in wireless body area networks for smart healthcare, in: Artificial Intelligence for Disease Diagnosis and Prognosis in Smart Healthcare, CRC Press, 2023, pp. 255-286.

[19] L. Zhang, P. Wang, Y. Zhang, Z. Chi, N. Tong, L. Wang, F. Li, An adaptive and ro-bust secret key extraction scheme from high noise wireless channel in IIoT, Digit.commun. Netw. 9 (4) (2023) 809-816.

[20] X. Yu, Y. Xie, Q. Xu, Z. Xu, R. Xiong, Secure data sharing for cross-domain industrial IoT based on consortium blockchain, in: 2023 26th International Conference on Com-puter Supported Cooperative Work in Design (CSCWD), IEEE, 2023, pp. 1508-1513.

[21] F. Tong, X. Chen, K. Wang, Y. Zhang, Ccap: a complete cross-domain authentication based on blockchain for internet of things, IEEE Trans. Inf. Forensics Secur. 17 (2022) 3789-3800.

[22] S. Zhang, Z. Yan, W. Liang, K.-C. Li, B. Di Martino, Bcae: A Blockchain-Based Cross Domain Authentication Scheme for Edge Computing, IEEE, 2024.

[23] J. Steinhardt, P.W. Koh, P.S. Liang, Certified defenses for data poisoning attacks, Adv. Neural Inf. Process. Syst. 30 (2017).

[24] R. Al Mallah, D. López, Blockchain-based monitoring for poison attack detection in decentralized federated learning, in: 2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), IEEE, 2022, pp. 1-6.

[25] W. Wang, S. Wang, D. Bai, C. Zhao, L. Peng, Z. Chen, Sfmd: a semi-supervised feder-ated malicious traffic detection approach in IoT, in: 2022 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/So-cialCom/SustainCom), IEEE, 2022, pp. 774-781.

[26] D. Luo, Y. Zhang, G. Sun, H. Yu, D. Niyato, An efficient consensus algorithm for blockchain-based cross-domain authentication in bandwidth-constrained wide-area IoT networks, IEEE Internet Things J. 11 (19) (2024) 31917-31931.

[27] C. Pu, I. Ahmed, S. Chakravarty, Resource-efficient and data type-aware authen-tication protocol for internet of things systems, in: 2023 5th IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA), IEEE, 2023, pp. 101-110.

[28] J. Cui, Y. Zhu, H. Zhong, Q. Zhang, C. Gu, D. He, Efficient blockchain-based mu-tual authentication and session key agreement for cross-domain IIoT, IEEE Internet Things J. 11 (9) (2024) 16325-16338.

[29] H. Zhang, X. Chen, X. Lan, H. Jin, Q. Cao, Btcas: a blockchain-based thoroughly cross-domain authentication scheme, J. Inf. Secur. Appl. 55 (2020) 102538.

[30] B. Chai, J. Yu, B. Yan, Y. Yu, S. Wang, BSCDA: blockchain-based secure cross-domain data access scheme for Internet of Things, IEEE Trans. Netw. Serv. Manag. 21 (4) (2024) 4006-4023.

[31] X. Jia, N. Hu, S. Su, S. Yin, Y. Zhao, X. Cheng, C. Zhang, Irba: an identity-based cross-domain authentication scheme for the internet of things, Electronics 9 (4) (2020) 634.

[32] B. McMahan, E. Moore, D. Ramage, S. Hampson, B.A. y Arcas, Communication-efficient learning of deep networks from decentralized data, in: Artificial Intelligence and Statistics, PMLR, 2017, pp. 1273-1282.

[33] T. ElGamal, A public key cryptosystem and a signature scheme based on discrete logarithms, IEEE Trans. Inf. Theory 31 (4) (1985) 469-472.

[34] M. Masud, G.S. Gaba, K. Choudhary, M.S. Hossain, M.F. Alhamid, G. Muhammad, Lightweight and anonymity-preserving user authentication scheme for IoT-based healthcare, IEEE Internet Things J. 9 (4) (2021) 2649-2656.

[35] M. Shen, H. Liu, L. Zhu, K. Xu, H. Yu, X. Du, M. Guizani, Blockchain-assisted secure device authentication for cross-domain industrial IoT, IEEE J. Sel. Areas Commun. 38 (5) (2020) 942-954.

[36] B. Hammi, A. Fayad, R. Khatoun, S. Zeadally, Y. Begriche, A lightweight ecc-based authentication scheme for internet of things (IoT), IEEE Syst. J. 14 (3) (2020) 3440-3450.

[37] E. Androulaki, A. Barger, V. Bortnikov, C. Cachin, K. Christidis, A. De Caro, D. Enyeart, C. Ferris, G. Laventman, Y. Manevich, et al., Hyperledger fabric: a dis-tributed operating system for permissioned blockchains,in: Proceedings of the Thir-teenth EuroSys Conference, 2018, pp. 1-15.

[38] M. Wang, C. Qian, X. Li, S. Shi, S. Chen, Collaborative validation of public-key certifi-cates for IoT by distributed caching, IEEE/ACM Trans. Netw. 29 (1) (2020) 92-105.