Skip to main content

Advertisement

Springer Nature Link
Log in

An improved PBFT consensus algorithm based on reputation and gaming

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

Blockchain technology provides a reliable and efficient environment for digital asset transactions. Consensus algorithms are the cornerstone of its security and accuracy. However, there are still security problems and performance bottlenecks associated with blockchain consensus algorithms in the context of current digital asset transactions, an improved PBFT algorithm (GamePBFT) based on reputation and game was proposed on the basis of Practical Byzantine Fault Tolerance (PBFT).Better applied to digital asset trading, we establish a reputation model that enables the dynamic reward and punishment of nodes according to their consensus behavior in this paper. Furthermore, a game model is constructed, which allows for the minimum number of nodes to participate in the consensus and the highest efficiency of eliminating malicious nodes. This can resist some common attacks, reduce the complexity of the algorithm, and improve the security and consensus efficiency of the algorithm. Finally, the results of the simulated node digital transaction scenario demonstrate that the improved consensus algorithm exhibits a notable enhancement over the PBFT consensus algorithm in terms of consensus latency, communication overhead, throughput, and security.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Data availability

No datasets were generated or analyzed during the current study.

References

  1. Jiménez I, Mora-Valencia A, Perote J (2023) Multivariate dynamics between emerging markets and digital asset markets: an application of the snp-dcc model. Emerg Mark Rev 56:101054

    Article  Google Scholar 

  2. Fang F, Ventre C, Basios M, Kanthan L, Martinez-Rego D, Wu F, Li L (2022) Cryptocurrency trading: a comprehensive survey. Financial Innov 8(1):13

    Article  Google Scholar 

  3. Xu J, Wang C, Jia X (2023) A survey of blockchain consensus protocols. ACM Comput Surv 55(13s):1–35

    Article  Google Scholar 

  4. Li C, Wang L, Yang H (2023) The optimal asset trading settlement based on proof-of-stake blockchains. Decis Support Syst 166:113909

    Article  Google Scholar 

  5. Jiang P, Zhang L, You S, Van Fan Y, Tan RR, Klemeš JJ, You F (2023) Blockchain technology applications in waste management: overview, challenges and opportunities. J Clean Product 421:138466

    Article  Google Scholar 

  6. Li W, Feng C, Zhang L, Xu H, Cao B, Imran MA (2020) A scalable multi-layer PBFT consensus for blockchain. IEEE Trans Parallel Distrib Syst 32(5):1146–1160

    Article  Google Scholar 

  7. Harish AR, Liu XL, Li M, Zhong RY, Huang GQ (2023) Blockchain-enabled digital assets tokenization for cyber-physical traceability in e-commerce logistics financing. Comput Indust 150:103956

    Article  Google Scholar 

  8. Kuhle P, Arroyo D, Schuster E (2021) Building a blockchain-based decentralized digital asset management system for commercial aircraft leasing. Comput Indust 126:103393

    Article  Google Scholar 

  9. Xu J, Zhao Y, Chen H, Deng W (2023) ABC-GSPBDF: PBFT with grouping score mechanism and optimized consensus process for flight operation data-sharing. Inform Sci 624:110–127

    Article  Google Scholar 

  10. Lao L, Dai X, Xiao B, Guo S (2020) G-PBFT: a location-based and scalable consensus protocol for iot-blockchain applications. In: 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 664–673 . IEEE

  11. Tang S, Wang Z, Jiang J, Ge S, Tan G (2022) Improved PBFT algorithm for high-frequency trading scenarios of alliance blockchain. Sci Reports 12(1):4426

    Google Scholar 

  12. Li Y, Wang Z, Fan J, Zheng Y, Luo Y, Deng C, Ding J (2019) An extensible consensus algorithm based on PBFT. In: 2019 International Conference on Cyber-enabled Distributed Computing and Knowledge Discovery (CyberC), pp. 17–23 . IEEE

  13. Tong W, Dong X, Zheng J (2019) Trust-PBFT: A peertrust-based practical byzantine consensus algorithm. In: 2019 International Conference on Networking and Network Applications (NaNA), pp. 344–349 . IEEE

  14. Chen Y, Li M, Zhu X, Fang K, Ren Q, Guo T, Chen X, Li C, Zou Z, Deng Y (2022) An improved algorithm for practical byzantine fault tolerance to large-scale consortium chain. Inform Process Manag 59(2):102884

    Article  Google Scholar 

  15. Xie M, Liu J, Chen S, Xu G, Lin M (2023) Primary node election based on probabilistic linguistic term set with confidence interval in the PBFT consensus mechanism for blockchain. Complex Intell Syst 9(2):1507–1524

    Article  Google Scholar 

  16. Fan H (2022) The digital asset value and currency supervision under deep learning and blockchain technology. J Comput Appl Math 407:114061

    Article  MathSciNet  Google Scholar 

  17. Min X, Kong L, Li Q, Liu Y, Zhang B, Zhao Y, Xiao Z, Guo B (2022) Blockchain-native mechanism supporting the circulation of complex physical assets. Comput Netw 202:108588

    Article  Google Scholar 

  18. Pang Y (2020) A new consensus protocol for blockchain interoperability architecture. IEEE Access 8:153719–153730

    Article  Google Scholar 

  19. Zhang S, Lee J-H (2020) Analysis of the main consensus protocols of blockchain. ICT Express 6(2):93–97

    Article  Google Scholar 

  20. Liu S, Zhang R, Liu C, Shi D (2023) P-PBFT: an improved blockchain algorithm to support large-scale pharmaceutical traceability. Comput Biol Med 154:106590

    Article  Google Scholar 

  21. Xiao J, Luo T, Li C, Zhou J, Li Z (2024) CE-PBFT: a high availability consensus algorithm for large-scale consortium blockchain. J King Saud Univ-Comput Inform Sci 36:101957

    Google Scholar 

  22. Zhu Z, Qi G, Zheng M, Sun J, Chai Y (2020) Blockchain based consensus checking in decentralized cloud storage. Simul Model Pract Theory 102:101987

    Article  Google Scholar 

  23. Kumar A, Vishwakarma L, Das D (2023) R-PBFT: a secure and intelligent consensus algorithm for internet of vehicles. Veh Commun 41:100609

    Google Scholar 

  24. Li C, Qiu W, Li X, Liu C, Zheng Z (2024) A dynamic adaptive framework for practical byzantine fault tolerance consensus protocol in the internet of things. IEEE Trans Comput 73:1669–1682

    Article  Google Scholar 

  25. Zhan Y, Wang B, Lu R, Yu Y (2021) DRBFT: delegated randomization byzantine fault tolerance consensus protocol for blockchains. Inform Sci 559:8–21

    Article  MathSciNet  Google Scholar 

  26. Zhang J, Yang Y, Zhao D, Wang Y (2023) A node selection algorithm with a genetic method based on PBFT in consortium blockchains. Complex Intell Syst 9(3):3085–3105

    Article  Google Scholar 

  27. Tang F, Xu T, Peng J, Gan N (2023) TP-PBFT: a scalable PBFT based on threshold proxy signature for IoT-blockchain applications. IEEE Int Things J 11:15434–15449

    Article  Google Scholar 

  28. Qushtom H, Mišić J, Chang X, Mišić VB (2021) A scalable two-tier pbft consensus for blockchain-based iot data recording. In: ICC 2021-IEEE International Conference on Communications, pp. 1–6 . IEEE

  29. Saad M, Spaulding J, Njilla L, Kamhoua C, Shetty S, Nyang D, Mohaisen A (2019) Exploring the attack surface of blockchain: a systematic overview. arXiv preprint arXiv:1904.03487

  30. Biryukov A, Feher D (2020) Recon: sybil-resistant consensus from reputation. Pervasive Mobile Comput 61:101109

    Article  Google Scholar 

  31. Erfan F, Bellaiche M, Halabi T (2023) Community detection algorithm for mitigating eclipse attacks on blockchain-enabled metaverse. In: 2023 IEEE International Conference on Metaverse Computing, Networking and Applications (MetaCom), pp. 403–407 . IEEE

  32. Karame GO, Androulaki E, Capkun S (2012) Double-spending fast payments in bitcoin. In: Proceedings of the 2012 ACM Conference on Computer and Communications Security, pp. 906–917

  33. Raikwar M, Gligoroski D (2021) Dos attacks on blockchain ecosystem. In: European Conference on Parallel Processing, pp. 230–242 . Springer

  34. Zhou S, Ying B (2021) Vg-raft: an improved byzantine fault tolerant algorithm based on raft algorithm. In: 2021 IEEE 21st International Conference on Communication Technology (ICCT), pp. 882–886 . IEEE

  35. Kumar R, Kumar P, Tripathi R, Gupta GP, Garg S, Hassan MM (2022) A distributed intrusion detection system to detect DDOS attacks in blockchain-enabled IoT network. J Parallel Distrib Comput 164:55–68

    Article  Google Scholar 

  36. Wang W, Wang L, Duan J, Tong X, Peng H (2024) Redactable blockchain based on decentralized trapdoor verifiable delay functions. IEEE Trans Inform Forensics Secur 19:7492–7507

    Article  Google Scholar 

  37. Gu C, Ma B, Hu D (2024) A dependable and efficient decentralized trust management system based on consortium blockchain for intelligent transportation systems. IEEE Trans Intell Transp Syst 25:19430–19443

    Article  Google Scholar 

  38. Wang P, Cao L, Hu Y, Sun Z (2024) Consensus algorithms based on collusion resistant publicly verifiable random number seeds. Comput Stand Inter 90:103853

    Article  Google Scholar 

  39. Liu J, Feng W, Huang M, Feng S, Zhang Y (2023) Grouped multilayer practical byzantine fault tolerance algorithm: a practical byzantine fault tolerance consensus algorithm optimized for digital asset trading scenarios. Sensors 23(21):8903

    Article  Google Scholar 

Download references

Funding

The work was supported by the National Key R&D Program of China under Grant (No. 2021YFB3300900), the National Natural Science Foundation of China (No. 62072336), the Key Research and Development Program of Tianjin (No. 23YFZCSN00240), and the Tianjin Technical Innovation Guidance Special Project (No. 22YDPYGX00040).

Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Tianjin University of Technology, No. 391 Binshui Xi Road, Xiqing District, Tianjin, 300384, China

    Zhe Li, Jinsong Wang & Yi Li

Authors
  1. Zhe Li
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Jinsong Wang
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Yi Li
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

Zhe Li contributed to conceptualization, methodology, software, validation, visualization, and writing—original draft preparation. Jinsong Wang contributed to funding acquisition, resources, and writing—review editing. Yi Li contributed to project administration, supervision, and writing—review editing.

Corresponding author

Correspondence to Jinsong Wang.

Ethics declarations

Conflict of interest

The authors declare no Conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, Z., Wang, J. & Li, Y. An improved PBFT consensus algorithm based on reputation and gaming. J Supercomput 81, 323 (2025). https://doi.org/10.1007/s11227-024-06822-2

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11227-024-06822-2

Keywords