Computer Science // 2022
A Survey of Vulnerability Detection Methods for Ethereum Solidity Smart Contracts
Yingli Zhang // Jiali Ma // Ziang Liu // Xin Liu // Rui Zhou
This survey reviews vulnerability detection methods for Ethereum Solidity smart contracts, covering representative vulnerability categories and mainstream techniques such as symbolic execution, fuzzing, formal verification, taint analysis, and more recent machine-learning based approaches.
Overview
This survey summarizes vulnerability detection methods for Ethereum Solidity smart contracts and organizes the technical landscape across symbolic execution, fuzzing, formal verification, taint analysis, and machine-learning based approaches.
Original published title: 以太坊Solidity智能合约漏洞检测方法综述.
Research context
The paper captures a literature-review oriented strand of work around blockchain security and vulnerability analysis, complementing system-building and empirical research in the rest of the archive.