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    ARTICLE

    Deep Learning-Based Program-Wide Binary Code Similarity for Smart Contracts

    Yuan Zhuang1, Baobao Wang1, Jianguo Sun2,*, Haoyang Liu1, Shuqi Yang1, Qingan Da3

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1011-1024, 2023, DOI:10.32604/cmc.2023.028058

    Abstract Recently, security issues of smart contracts are arising great attention due to the enormous financial loss caused by vulnerability attacks. There is an increasing need to detect similar codes for hunting vulnerability with the increase of critical security issues in smart contracts. Binary similarity detection that quantitatively measures the given code diffing has been widely adopted to facilitate critical security analysis. However, due to the difference between common programs and smart contract, such as diversity of bytecode generation and highly code homogeneity, directly adopting existing graph matching and machine learning based techniques to smart contracts suffers from low accuracy, poor… More >

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