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DIAM

This repository is an official PyTorch(Geometric) implementation of DIAM in "Effective Illicit Account Detection on Large Directed MultiGraph Transaction Networks of Cryptocurrencies".

Framework

Requirements

  • 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

Data

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

Usage

  1. Download and extract data files to /data folder.

  2. Generate edge sequences.

    python3 preprocess.py

  3. Run DIAM.

    python3 main.py

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