Unveiling Smart Contracts Vulnerabilities: Toward Profiling Smart Contracts Vulnerabilities using Enhanced Genetic Algorithm and Generating Benchmark Dataset
Smart Contracts (SCs) are critical in blockchain but remain vulnerable, with existing detection methods often lacking accuracy and scalability. We propose SCsVulLyzer V2.0, an analyzer extracting 240 features, combined with a Genetic Algorithm (GA)-based profiling method that leverages adaptive mutation, elite retention, and penalty fitness functions for precise vulnerability profiling. Validated with the new BCCC-SCsVul-2024 dataset of 111,897 Solidity contracts, our approach achieves higher precision, efficiency, and explainability, advancing SC vulnerability detection and profiling.