Smart Contract Vulnerability Detection: A Systematic Literature Review

Abstract

Blockchain technology allows us to make trust-based transactions without third-party intermediaries. However, its rapidly developing nature brings serious security vulnerabilities. These vulnerabilities are a research priority because smart contracts (SC) maintained on the blockchain system cannot be modified or reversed after deployment. Our research indicates that Deep Learning (DL) and Machine Learning (ML) methodologies have recently become popular for detecting these vulnerabilities in SC. This systematic literature evaluation highlights its contributions compared to similar studies with the most common vulnerabilities.