Dual-view Aware Smart Contract Vulnerability Detection for Ethereum

TL;DR

This paper introduces DVDet, a dual-view framework that converts smart contract code and bytecode into graphs and sequences to improve vulnerability detection accuracy on Ethereum.

Contribution

The paper presents a novel dual-view analysis framework combining source code and bytecode for enhanced smart contract vulnerability detection.

Findings

DVDet outperforms existing methods in vulnerability detection accuracy.

The dual-view approach effectively captures risk features from code and bytecode.

Experimental results demonstrate the framework's robustness and effectiveness.

Abstract

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.