Smart Contract Vulnerability Detection Model Based on Siamese Network (SCVSN): A Case Study of Reentrancy Vulnerability

【Author】 Guo, Ran; Chen, Weijie; Zhang, Lejun; Wang, Guopeng; Chen, Huiling

【Source】ENERGIES

【影响因子】3.252

【Abstract】Blockchain technology is currently evolving rapidly, and smart contracts are the hallmark of the second generation of blockchains. Currently, smart contracts are gradually being used in power system networks to build a decentralized energy system. Security is very important to power systems and attacks launched against smart contract vulnerabilities occur frequently, seriously affecting the development of the smart contract ecosystem. Current smart contract vulnerability detection tools suffer from low correct rates and high false positive rates, which cannot meet current needs. Therefore, we propose a smart contract vulnerability detection system based on the Siamese network in this paper. We improved the original Siamese network model to perform smart contract vulnerability detection by comparing the similarity of two sub networks with the same structure and shared parameters. We also demonstrate, through extensive experiments, that the model has better vulnerability detection performance and lower false alarm rate compared with previous research results.

【Keywords】smart contract; deep learning; siamese network

【发表时间】2022 DEC

【收录时间】2023-01-16

【文献类型】实验仿真

【主题类别】

区块链治理-技术治理-智能合约漏洞检测