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Volume 12 Issue 7
Jul.  2025

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2025  >  12(7): 1407-1417
J. Zhu, C. Lu, J. Li, and F.-Y. Wang, “Secure consensus control on multi-agent systems based on improved PBFT and Raft blockchain consensus algorithms,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 7, pp. 1407–1417, Jul. 2025. doi: 10.1109/JAS.2025.125300
Citation: J. Zhu, C. Lu, J. Li, and F.-Y. Wang, “Secure consensus control on multi-agent systems based on improved PBFT and Raft blockchain consensus algorithms,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 7, pp. 1407–1417, Jul. 2025. doi: 10.1109/JAS.2025.125300
shu

Secure Consensus Control on Multi-Agent Systems Based on Improved PBFT and Raft Blockchain Consensus Algorithms

doi: 10.1109/JAS.2025.125300
Funds:  This work was partly supported by the Fundamental Research Funds for the Central Universities (NS2024021), the Science and Technology Development Fund of Macau SAR (0145/2023/RIA3, 0093/2023/RIA2, 0050/2020/A1), and the National Natural Science Foundation of China (62103411)
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    Abstract
  • There has been significant recent research on secure control problems that arise from the open and complex real-world industrial environments. This paper focuses on addressing the issue of secure consensus control in multi-agent systems (MASs) under malicious attacks, utilizing the practical Byzantine fault tolerance (PBFT) and Raft consensus algorithm in blockchain. Unlike existing secure consensus control algorithms that have strict requirements for topology and high communication costs, our approach introduces a node grouping methodology based on system topology. Additionally, we utilize the PBFT consensus algorithm for intergroup leader identity verification, effectively reducing the communication complexity of PBFT in large-scale networks. Furthermore, we enhance the Raft algorithm through cryptographic validation during followers’ log replication, which enhances the security of the system. Our proposed consensus process not only identifies the identities of malicious agents but also ensures consensus among normal agents. Through extensive simulations, we demonstrate robust convergence, particularly in scenarios with the relaxed topological requirements. Comparative experiments also validate the algorithm’s lower consensus latency and improved efficiency compared to direct PBFT utilization for identity verification and classical secure consensus control method mean subsequence reduced (MSR) algorithm.

     

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  • [1]
    S. Bijani and D. Robertson, “A review of attacks and security approaches in open multi-agent systems,” Artificial Intelligence Review, vol. 42, pp. 607–636, 2014. doi: 10.1007/s10462-012-9343-1
    [2]
    W. He, W. Xu, X. Ge, Q.-L. Han, W. Du, and F. Qian, “Secure control of multiagent systems against malicious attacks: A brief survey,” IEEE Trans. on Industrial Inform., vol. 18, no. 6, pp. 3595–3608, 2022. doi: 10.1109/TII.2021.3126644
    [3]
    Y. Wu, X. He, and S. Liu, “Resilient consensus for multi-agent systems with quantized communication,” in Proc. IEEE American Control Conf., 2016, pp. 5136–5140.
    [4]
    R. Olfati-Saber, J. A. Fax, and R. M. Murray, “Consensus and cooperation in networked multi-agent systems,” Proc. IEEE, vol. 95, no. 1, pp. 215–233, 2007. doi: 10.1109/JPROC.2006.887293
    [5]
    S. Liu, H. Zhu, S. Li, X. Li, C. Chen, and X. Guan, “An adaptive deviation-tolerant secure scheme for distributed cooperative spectrum sensing,” in Proc. IEEE Global Communi. Conf., 2012, pp. 603–608.
    [6]
    C. Zhao, J. He, and J. Chen, “Resilient consensus with mobile detectors against malicious attacks,” IEEE Trans. Signal and Information Processing Over Networks, vol. 4, no. 1, pp. 60–69, 2017.
    [7]
    H. J. LeBlanc and X. Koutsoukos, “Resilient first-order consensus and weakly stable, higher order synchronization of continuous-time networked multiagent systems,” IEEE Trans. Control Network Systems, vol. 5, no. 3, pp. 1219–1231, 2017.
    [8]
    M. Yampolskiy, Y. Vorobeychik, X. D. Koutsoukos, P. Horvath, H. J. LeBlanc, and J. Sztipanovits, “Resilient distributed consensus for tree topology,” in Proc. 3rd Int. Conf. High Confidence Networked Systems, 2014, pp. 41–48.
    [9]
    H. J. LeBlanc, H. Zhang, X. Koutsoukos, and S. Sundaram, “Resilient asymptotic consensus in robust networks,” IEEE J. Selected Areas in Communi., vol. 31, no. 4, pp. 766–781, 2013. doi: 10.1109/JSAC.2013.130413
    [10]
    Y. Wu and X. He, “Secure consensus control for multiagent systems with attacks and communication delays,” IEEE/CAA J. Autom. Sinica, vol. 4, no. 1, pp. 136–142, 2017. doi: 10.1109/JAS.2016.7510010
    [11]
    W. Abbas, A. Laszka, Y. Vorobeychik, and X. Koutsoukos, “Improving network connectivity using trusted nodes and edges,” in Proc. IEEE American Control Conf., 2017, pp. 328–333.
    [12]
    J. Huang, Y. Wu, L. Chang, M. Tao, and X. He, “Resilient consensus with switching networks and heterogeneous agents,” Neurocomputing, vol. 341, pp. 70–79, 2019. doi: 10.1016/j.neucom.2019.03.018
    [13]
    Q.-L. Han, “Editorial: Secure and safe metacontrol for cyber physical systems,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 12, pp. 2177–2178, 2023. doi: 10.1109/JAS.2023.124014
    [14]
    J. Li and F.-Y. Wang, “The tao of blockchain intelligence for intelligent web 3.0,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 12, pp. 2183–2186, 2023. doi: 10.1109/JAS.2023.124056
    [15]
    S. K. Dwivedi, R. Amin, and S. Vollala, “Blockchain-based secured ipfsenable event storage technique with authentication protocol in vanet,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 12, pp. 1913–1922, 2021. doi: 10.1109/JAS.2021.1004225
    [16]
    F.-Y. Wang, R. Qin, Y. Chen, Y. Tian, X. Wang, and B. Hu, “Federated ecology: Steps toward confederated intelligence,” IEEE Trans. Computational Social Systems, vol. 8, no. 2, pp. 271–278, 2021. doi: 10.1109/TCSS.2021.3063801
    [17]
    F.-Y. Wang, R. Qin, J. Li, X. Wang, H. Qi, X. Jia, and B. Hu, “Federated management: Toward federated services and federated security in federated ecology,” IEEE Trans. Computational Social Systems, vol. 8, no. 6, pp. 1283–1290, 2021. doi: 10.1109/TCSS.2021.3125312
    [18]
    F.-Y. Wang, J. Zhu, R. Qin, X. Wang, and B. Hu, “Federated control: Toward information security and rights protection,” IEEE Trans. Computational Social Systems, vol. 8, no. 4, pp. 793–798, 2021. doi: 10.1109/TCSS.2021.3094655
    [19]
    X. Deng, K. Li, Z. Wang, J. Li, and Z. Luo, “A survey of blockchain consensus algorithms,” in Proc. IEEE Int. Conf. Blockchain Technology and Infor. Security, 2022, pp. 188–192.
    [20]
    J. Li and T. Wolf, “A one-way proof-of-work protocol to protect controllers in software-defined networks,” in Proc. Architectures for Networking and Communi. Systems, 2016, pp. 123–124.
    [21]
    C. Ganesh, C. Orlandi, and D. Tschudi, “Proof-of-stake protocols for privacy-aware blockchains,” in Proc. Advances in Cryptology–EUROCRYPT 38th Annual International Conf. the Theory and Applications of Cryptographic Techniques, Darmstadt, Germany. Springer, 2019, Proceedings, Part I 38, pp. 690–719.
    [22]
    F. Yang, W. Zhou, Q. Wu, R. Long, N. N. Xiong, and M. Zhou, “Delegated proof of stake with downgrade: A secure and efficient blockchain consensus algorithm with downgrade mechanism,” IEEE Access, vol. 7, p. 118, 2019.
    [23]
    I. Bentov, C. Lee, A. Mizrahi, and M. Rosenfeld, “Proof of activity: Extending bitcoin’s proof of work via proof of stake [extended abstract],” ACM SIGMETRICS Performance Evaluation Review, vol. 42, no. 3, pp. 34–37, 2014. doi: 10.1145/2695533.2695545
    [24]
    Y. Gilad, R. Hemo, S. Micali, G. Vlachos, and N. Zeldovich, “Algorand: Scaling byzantine agreements for cryptocurrencies,” in Proc. 26th Symp. Operating Systems Principles, 2017, pp. 51–68.
    [25]
    L. Lamport, R. Shostak, and M. Pease, “The byzantine generals problem,” ACM Trans. Programming Languages and Systems, vol. 4, no. 3, pp. 382–401, 1982.
    [26]
    M. Castro and B. Liskov, “Practical byzantine fault tolerance and proactive recovery,” ACM Trans. Computer Systems, vol. 20, no. 4, pp. 398–461, 2002. doi: 10.1145/571637.571640
    [27]
    N. H. Vaidya, L. Tseng, and G. Liang, “Iterative approximate byzantine consensus in arbitrary directed graphs,” in Proc. ACM Symp. Principles of Distributed Computing, 2012, pp. 365–374.
    [28]
    D. Ongaro and J. Ousterhout, “In search of an understandable consensus algorithm (extended version),” in Proc. USENIX Annual Technical Conf., 2014, pp. 19–20.
    [29]
    R. Olfati-Saber and R. M. Murray, “Consensus problems in networks of agents with switching topology and time-delays,” IEEE Trans. Autom. Control, vol. 49, no. 9, pp. 1520–1533, 2004. doi: 10.1109/TAC.2004.834113
    [30]
    T. Han and J. Xie, “Rsa encryption and decryption algorithm and related attack methods,” Computer and Information Technology, vol. 26, no. 1, 2018.
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