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Prevention method of block withholding attack based on miners’ mining behavior in blockchain

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Abstract

This paper proposes a prevention method of block withholding attack (PMBWA) based on miners’ mining behavior in blockchain to prevent the block withholding attack. The PMBWA first performs the data pre-processing based on the box chart detection algorithm for data cleaning and preliminary verification. Then the PMBWA uses the behavior reward, punishment mechanism, and credit model to comprehensively evaluate the contribution of miners. The PMBWA proposes a credit level classification algorithm (CLCA) of miners that weighs posterior probability and similarity to detect the malicious miners. Finally, the PMBWA allocates the corresponding income weight for miners of different credit levels. The simulation results show that regardless of how the numbers of blocks and malicious computing power change, the PMBWA can allocate low-income weight to the corresponding malicious computing power, and significantly improve the precision rate and recall rate of malicious computing power detection in the defensive mining pool. The PMBWA can largely reduce the average cumulative income of malicious computing power and improve the average cumulative income of non-malicious computing power. The PMBWA outperforms the state-of-the-art methods such as ICIAS, SRIAS, and IASCM.

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Data Availability

The data that support the findings of this study are available from Zhejiang Shuren University but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of Zhejiang Shuren University.

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Funding

This work was supported by the “Ling Yan” Research and Development Project of Science and Technology Department in Zhejiang Province of China under Grants No. 2022C03122, Public Welfare Technology Application and Research Projects in Zhejiang Province of China under Grants No. LGF22F020006 and LGF21F010004, and Project Intelligentization and Digitization for Airline Revolution No. 2018R02008.

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Authors and Affiliations

  1. The College of Information Science and Technology, Zhejiang Shuren University, Hangzhou, 310015, Zhejiang, China

    Hao Chen, Yourong Chen, Banteng Liu & Zhangquan Wang

  2. The College of Electronics and Information, Hangzhou Dianzi University, Hangzhou, 310018, Zhejiang, China

    Hao Chen

  3. Viterbi School of Engineering, University of Southern California, Los Angeles, 90089-0911, CA, USA

    Zhenyu Xiong

  4. Binjiang Insititute of Zhejiang University, Hangzhou, 310053, China

    Meng Han

  5. Zhejiang Juntong Intelligence Co. Ltd, Hangzhou, 310053, China

    Meng Han

  6. Jinan University, Guangzhou, 510000, Guangdong, China

    Zaobo He

  7. The School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou, 213164, Jiangsu, China

    Zhenghua Ma

Authors
  1. Hao Chen
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  2. Yourong Chen
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  3. Zhenyu Xiong
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  4. Meng Han
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  5. Zaobo He
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  6. Banteng Liu
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  7. Zhangquan Wang
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  8. Zhenghua Ma
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Contributions

HC, YC and ZY wrote the entire paper. MH, ZH and BL are responsible for the algorithm principles. ZW and ZM are responsible for algorithm implementation.

Corresponding author

Correspondence to Yourong Chen.

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Chen, H., Chen, Y., Xiong, Z. et al. Prevention method of block withholding attack based on miners’ mining behavior in blockchain. Appl Intell 53, 9878–9896 (2023). https://doi.org/10.1007/s10489-022-03889-3

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