Proceedings of the 3rd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2024, March 29–31, 2024, Wuhan, China

Research Article

Research on Smart Contract Vulnerability Detection Technology Based on VCS and Ensemble Learning

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  • @INPROCEEDINGS{10.4108/eai.29-3-2024.2347453,
        author={Shouhan  Wei},
        title={Research on Smart Contract Vulnerability Detection Technology Based on VCS and Ensemble Learning},
        proceedings={Proceedings of the 3rd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2024, March 29--31, 2024, Wuhan, China},
        publisher={EAI},
        proceedings_a={ICBBEM},
        year={2024},
        month={6},
        keywords={smart contract; vulnerability detection; deep learning; ensemble learning},
        doi={10.4108/eai.29-3-2024.2347453}
    }
    
  • Shouhan Wei
    Year: 2024
    Research on Smart Contract Vulnerability Detection Technology Based on VCS and Ensemble Learning
    ICBBEM
    EAI
    DOI: 10.4108/eai.29-3-2024.2347453
Shouhan Wei1,*
  • 1: Jiangxi University of Science and Technology
*Contact email: 1289382022@qq.com

Abstract

Smart contracts play a crucial role in blockchain technology, but their writing poses risks of vulnerabilities, potentially leading to serious consequences such as financial losses and system crashes. To address this, we propose a smart contract vulnerability detection method based on VCS and ensemble learning. This method first utilizes Vulnerability Candidate Slicing (VCS) technology to extract syntax and semantic features, enhancing detection capabilities. Then, it employs Word2vec, FastText, GloVe, and other embedding models to transform raw inputs into vector representations, capturing more semantic information. Finally, an ensemble learning strategy integrates multiple neural network models to improve detection performance and mitigate the limitations of individual models. Experimental results demonstrate that this method outperforms other advanced tools in the market, providing robust support for ensuring the security and stability of blockchain systems.