Dataset for Reseach Paper (RPHunter: Unveiling Rug Pull Schemes in Crypto Token via Code-and-Transaction Fusion Analysis)

This is a repository that contains the dataset of our paper in the support of the Research Paper submission. RPHunter is a novel technique that models code risk information and suspicious transaction behavior within two graph structures, utilizing graph neural networks (GNNs) for feature learning to enhance Rug Pull detection across varied scenarios. We have conducted an empirical study to uncover the underlying mechanisms of Rug Pull by analyzing 645 real-world Rug Pull incidents