The BCCC-VulSCs-2023 dataset is a substantial collection for Solidity Smart Contracts (SCs) analysis, comprising 36,670 samples, each enriched with 70 feature columns. These features include the raw source code of the smart contract, a hashed version of the source code for secure referencing, and a binary label that indicates a contract as secure (0) or vulnerable (1). The dataset's extensive size and comprehensive features make it a valuable resource for machine-learning models to predict contract behavior, identify patterns, or classify contracts based on security and functionality criteria.
The full research paper outlining the details of the dataset and its underlying principles:
“Unveiling Vulnerable Smart Contracts: Toward Profiling Vulnerable Smart Contracts using Genetic Algorithm and Generating Benchmark Dataset”, Sepideh Hajihosseinkhani, Arash Habibi Lashkari, Ali Mizani, Blockchain: Research and Applications, Vol. 4, 2023
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