DataBarrels.ipynb - ноутбук с EDA (исследование и визуализация данных) и обучением модели
Parsing Data.py - пример сбора тестовых данных из API blockchain
ModelDir.zip - веса обученной графовой нейронной сети
- Joana Lorenz, Maria Inês Silva, David Aparício, João Tiago Ascensão, Pedro Bizarro: “Machine learning methods to detect money laundering in the Bitcoin blockchain in the presence of label scarcity”, 2020; arXiv:2005.14635.
- Fredrik Johannessen, Martin Jullum: “Finding Money Launderers Using Heterogeneous Graph Neural Networks”, 2023; arXiv:2307.13499.
- Adam Goodge, Bryan Hooi, See Kiong Ng, Wee Siong Ng: “LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks”, 2021; arXiv:2112.05355.
- Kun Yang, Samory Kpotufe, Nick Feamster: “An Efficient One-Class SVM for Anomaly Detection in the Internet of Things”, 2021; arXiv:2104.11146.
- Hongzuo Xu, Guansong Pang, Yijie Wang, Yongjun Wang: “Deep Isolation Forest for Anomaly Detection”, 2022; arXiv:2206.06602. DOI: 10.1109/TKDE.2023.3270293.