A statistical framework for graph anomaly detection
SFGAD is a tool for detecting anomalies in graph and graph streams with python.
- Efficient computation of graph features
- Statistical models for detecting anomalous behavior
- Graph scanning to detect connected graph anomalies
- A customizable detection framework with 6 components
- Several pre-defined configurations
- Python: 3.5 or higher
- NumPy: 1.8.2 or higher
- SciPy: 0.13.3 or higher
- Pandas: 0.22.0 or higher
- NetworkX: 1.11.0 or higher
Installation (coming soon)
Installation of the latest release is available at the Python package index and on conda.
conda install sfgad
pip install sfgad
The source code is currently available on GitHub: https://github.com/sudrich/sf-gad
For testing use pytest from the source directory:
This work originated from the QuestMiner project (grant no. 01IS12051) and was partially funded by the German Federal Ministry of Education and Research (BMBF).
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