Bitcoin-Laundering-Identification

This repository provides a reference implementation of HBTBD as described in the paper:

Bitcoin Laundering Identification Method Based on Heterogeneous Graph Metapath Encoder

Dependencies

Recent versions of the following packages for Python 3 are required:

• PyTorch 1.2.0
• DGL 0.3.1
• NetworkX 2.3
• scikit-learn 0.21.3
• NumPy 1.17.2
• SciPy 1.3.1

Dependencies for the preprocessing code are not listed here.

Datasets

The preprocessed datasets are available at:

• HBTBD - [Kaggle]https://www.kaggle.com/datasets/songjialin/hbtbd-for-aml)

Usage

1. Create checkpoint/ and data/preprocessed directories
2. Extract the zip file downloaded from the section above to data/preprocessed
3. Execute one of the following three commands from the project home directory:
   • python run_Elliptic.py