Bytecode-based Image Analysis for Security Vulnerability Detection in Ethereum Smart Contracts

Abstract

This paper underscores the vital role of blockchain technology in Industry 4.0, aiming to inspire researchers and industry professionals to recognize its transformative potential in creating decentralized, automated, and data-driven industrial settings. It explains core concepts, components, and varieties of blockchain systems, and assesses their uses across various sectors. The research delves into security and privacy issues, particularly relating to Ethereum platforms and smart contracts. It meticulously details common vulnerabilities of smart contracts and their implications for industrial systems. A critical comparison of existing vulnerability-detection techniques reveals current limitations. The paper also investigates the potential of artificial intelligence to enhance security analysis in blockchain contexts, systematically reviewing machine learning and deep learning strategies for identifying smart contract issues. A novel detection framework is introduced and tested against real-world datasets, showing improved accuracy and robustness compared to traditional methods. Ultimately, the paper aims to foster the development of secure and trustworthy blockchain infrastructure for applications in Industry 4.0.