This repository is an official PyTorch(Geometric) implementation of DIAM in "Effective Illicit Account Detection on Large Directed MultiGraph Transaction Networks of Cryptocurrencies".
- Python==3.9
- torch==1.12.0+cu116
- torch-geometric==2.2.0
- scikit-learn==1.1.1
- scipy==1.8.1
- numpy==1.22.4
- dgl-cu116==0.8.2.post1
| Dataset | #Nodes | #Edges | #Edge attribute | #Illicit | #Normal | Illicit:Normal |
|---|---|---|---|---|---|---|
| Ethereum-S | 1,329,729 | 6,794,521 | 2 | 1,660 | 1,700 | 1:1.02 |
| Ethereum-P | 2,973,489 | 13,551,303 | 2 | 1,165 | 3,418 | 1:2.93 |
| Bitcoin-M | 2,505,841 | 14,181,316 | 5 | 46,930 | 213,026 | 1:4.54 |
| Bitcoin-L | 20,085,231 | 203,419,765 | 8 | 362,391 | 1,271,556 | 1: 3.51 |
The four datasets can be downloaded here: datasets
-
Download and extract data files to
/datafolder. -
Generate edge sequences.
python3 preprocess.py -
Run DIAM.
python3 main.py
