This is a PYG implementation of I2BGNN, as described in the following:
Identity inference on blockchain using graph neural network
For hardware configuration, the experiments are conducted at Ubuntu 18.04.5 LTS with the Intel(R) Xeon(R) Gold 5218R CPU @ 2.10GHz, and NVIDIA Tesla V100S GPU (with 40GB memory each). For software configuration, all model are implemented in
- Python 3.7
- Pytorch-Geometric 2.0.3
- Pytorch 1.8.0
- Scikit-learn 0.24.1
- CUDA 10.2
Download data from this link and place it under the 'data/eth/' path.
Execute the following bash commands in the same directory where the code resides:
$ python main.py -l p --hop 2 -ess Volume -layer 2 --pooling max --hidden_dim 128 --batch_size 32 --lr 0.001 --dropout 0.2 -undir 1 -which_ew VolumeMore parameter settings can be found in 'utils/parameters.py'.
If you find this work useful, please cite the following:
@inproceedings{shen2021identity,
title={Identity inference on blockchain using graph neural network},
author={Shen, Jie and Zhou, Jiajun and Xie, Yunyi and Yu, Shanqing and Xuan, Qi},
booktitle={International Conference on Blockchain and Trustworthy Systems},
pages={3--17},
year={2021},
organization={Springer}
}