fesevu/ethereum_fraud_dataset_by_activity
๐ธ Ethereum Address Behavior Dataset โ GNN + LSTM (Fraud Detection) This dataset is designed for fraud detection on Ethereum addresses using a dual-modality approach: Graph Neural Networks (GNN): transaction graph structure. Recurrent Models (LSTM/Transformers): time-series of address features. The dataset is built from: Ethereum public BigQuery dataset (bigquery-public-data.crypto_ethereum.transactions). Etherscan labels + custom scam labels. Balanced address list of ~115kโฆ See the full description on the dataset page: https://huggingface.co/datasets/fesevu/ethereum_fraud_dataset_by_activity.
| Author / organization | fesevu |
|---|---|
| License (as declared) | cc-by-4.0 |
| Downloads | 866 (as reported by Hugging Face) |
| Likes | 1 |
| Created | 26 August 2025 |
| Last updated at source | 27 August 2025 |
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