Fuzzing Based Approach for Vulnerability Detection in Smart Contracts

Abstract

Smart contracts are programs that work on blockchain technology and are designed to automatically perform certain operations. Today, smart contracts, especially Ethereum-based ones, are widely used in various fields such as finance, healthcare, supply chain and property management. Unlike traditional contracts, these contracts offer the advantage of executing transactions securely and transparently without the need for any intermediaries. However, due to their security vulnerabilities, they carry the risk of being exploited by malicious attackers. This work proposes a fuzzing-based approach to detect vulnerabilities in smart contracts. The proposed method aims to identify unknown or overlooked potential security vulnerabilities by enabling automatic testing of smart contracts. Within the scope of the study, different fuzzing-based analysis techniques were compared, the advantages and disadvantages of these methods were evaluated. The findings reveal that fuzzing-based testing techniques can be an effective tool in improving the security of smart contracts.