Awesome
MIDAS
<p> <a href="https://github.com/Stream-AD/MIDAS/blob/master/LICENSE"> <img src="https://img.shields.io/badge/License-Apache%202.0-blue.svg"> </a> </p>This repo is forked from Stream-AD/MIDAS. The core is written in C++. This repo added a Python wrapper to it.
Blog post: https://blog.munhou.com/2021/03/27/Network-Anomaly-Detection-with%20MIDAS-MIDAS-R-and-MIDAS-F/
Requirements
- Cmake >= 3.15
- C++11
- C++ standard libraries
Installation
- Make sure you clone this repo with
--recursive
- Open a terminal
cd
to the project rootMIDAS/
- Install with pip:
pip install .
- Run following code to test.
from MIDAS import MIDAS, MIDASR, MIDASF
num_row = 2
num_col = 1024
factor = 0.5
threshold = 1e3
midas = MIDAS(num_row=num_row, num_col=num_col)
midas_r = MIDASR(num_row=num_row, num_col=num_col, factor=factor)
midas_f = MIDASF(num_row=num_row, num_col=num_col, threshold=threshold, factor=factor)
example_source = 3
example_destination = 5
example_timestamp = 1
score = midas.add_edge(source=example_source, destination=example_destination, timestamp=example_timestamp)
score_r = midas_r.add_edge(source=example_source, destination=example_destination, timestamp=example_timestamp)
score_f = midas_f.add_edge(source=example_source, destination=example_destination, timestamp=example_timestamp)
# dump model
midas.dump('midas.json')
midas_r.dump('midas_r.json')
midas_f.dump('midas_f.json')
# load model
midas = MIDAS.load('midas.json')
midas_r = MIDASR.load('midas_r.json')
midas_f = MIDASF.load('midas_f.json')
Citation
If you use this code for your research, please consider citing the original authors' arXiv preprint
@misc{bhatia2020realtime,
title={Real-Time Streaming Anomaly Detection in Dynamic Graphs},
author={Siddharth Bhatia and Rui Liu and Bryan Hooi and Minji Yoon and Kijung Shin and Christos Faloutsos},
year={2020},
eprint={2009.08452},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
or their AAAI paper
@inproceedings{bhatia2020midas,
title="MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams",
author="Siddharth {Bhatia} and Bryan {Hooi} and Minji {Yoon} and Kijung {Shin} and Christos {Faloutsos}",
booktitle="AAAI 2020 : The Thirty-Fourth AAAI Conference on Artificial Intelligence",
year="2020"
}