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Unveiling vulnerable smart contracts:Toward profiling vulnerable smart contracts using genetic algorithm and generating benchmark dataset

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Blockchain(Research and Applications) 2024年第1期5卷 58-84页

作者： sepideh hajihosseinkhani Arash Habibi Lashkari Ali Mizani Oskui Computer Science Department of Computer Science and EngineeringYork UniversityTorontoOntario M3J1P3Canada Behavior-Centric Cybersecurity Center(BCCC) School of Information TechnologyYork UniversityTorontoOntario M3J1P3Canada Financial and Crypto Advisory of Switzerland(FiCAS AG) ZugSwitzerland

Smart contracts(SCs)are crucial in maintaining trust within blockchain ***,existing methods for analyzing SC vulnerabilities often lack accuracy and effectiveness,while approaches based on Deep Neural Networks(DNNs)struggle with detecting complex vulnerabilities due to limited data *** paper proposes a novel approach for analyzing SC *** method leverages an advanced form of the Genetic Algorithm(GA)and includes the development of a comprehensive benchmark dataset consisting of 36,670 Solidity source code *** primary objective of our study is to profile vulnerable SCs *** achieve this goal,we have devised an analyzer called SCsVulLyzer based on GAs,designed explicitly for profiling ***,we have carefully curated a new dataset encompassing a wide range of examples,ensuring the practical validation of our ***,we have established three distinct taxonomies that cover SCs,profiling techniques,and feature *** taxonomies provide a systematic classification and analysis of information,improving the efficiency of our *** methodology underwent rigorous testing through experimentation,and the results demonstrated the superior capabilities of our model in detecting *** to traditional and DNN-based approaches,our approach achieved higher precision,recall,and F1-score,which are widely used metrics for evaluating model *** all these metrics,our model showed exceptional *** customization and adaptations we implemented within the GA significantly enhanced its *** approach detects SC vulnerabilities more efficiently and facilitates robust *** promising results highlight the potential of GA-based profiling to improve the detection of SC vulnerabilities,contributing to enhanced security in blockchain networks.

关键词： Smart contracts(SCs) Vulnerability Vulnerable smart contracts Vulnerability profiling Genetic algorithm

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