Dual-view Aware Smart Contract Vulnerability Detection for Ethereum
This addresses security challenges for blockchain users and developers, but appears incremental as it builds on existing detection techniques with a hybrid approach.
The paper tackled the problem of detecting vulnerabilities in Ethereum smart contracts by proposing a dual-view framework that analyzes source code and bytecode, achieving effective detection and outperforming other methods in experiments.
The wide application of Ethereum technology has brought technological innovation to traditional industries. As one of Ethereum's core applications, smart contracts utilize diverse contract codes to meet various functional needs and have gained widespread use. However, the non-tamperability of smart contracts, coupled with vulnerabilities caused by natural flaws or human errors, has brought unprecedented challenges to blockchain security. Therefore, in order to ensure the healthy development of blockchain technology and the stability of the blockchain community, it is particularly important to study the vulnerability detection techniques for smart contracts. In this paper, we propose a Dual-view Aware Smart Contract Vulnerability Detection Framework named DVDet. The framework initially converts the source code and bytecode of smart contracts into weighted graphs and control flow sequences, capturing potential risk features from these two perspectives and integrating them for analysis, ultimately achieving effective contract vulnerability detection. Comprehensive experiments on the Ethereum dataset show that our method outperforms others in detecting vulnerabilities.