关键词: 区块链, 智能合约安全, 漏洞检测, 漏洞修复, 机器学习

Abstract: The smart contract is a fundamental technology of blockchain, as it operates without the need for third-party authorities and can directly provide trusted customized services to users. It represents an important advancement in blockchain technology. As the application range of smart contracts continues to expand, ensuring their safe and reliable operation has become a pressing issue in the field of blockchain security. This paper first examines vulnerability detection of smart contracts using machine learning, analyzing and summarizing different types of vulnerabilities, the status of data sets, classification methods, and advantages and disadvantages of existing model approaches. It also proposes the idea of creating high-quality data sets for smart contracts by combining static analysis tools with trust learning. Additionally, this paper introduces existing schemes for repairing smart contract vulnerabilities, comprehensively comparing their advantages and disadvantages while summarizing related technologies that could be used in future smart contract vulnerability repair efforts. Finally, it analyzes current issues and prospects future research directions for smart contract security.

Key words: blockchain, smart contract security, vulnerability detection, vulnerability repair, machine learning