Source code for ToN'21 paper: "Interactive Anomaly Detection in Dynamic Communication Networks".
- python: 3.9
- numpy: 1.25.0
- pandas: 2.0.2
- matplotlib: 3.7.2
- scikit-learn: 1.3.0
- seaborn: 0.12.0
- tqdm: 4.65.0
- Run the code with sample data extracted from CICIDS2017.
python3 ucb_haddn.py
- Labeling results of the time period
t
andt+1
can be found in./ucb_old.csv
and./ucb_new.csv
, and the anomaly detection results of the time periodt+1
can be found in./ucb_test.csv
.
- Run the code
python3 ts_haddn.py
- Labeling results of the time period
t
andt+1
can be found in./ts_old.csv
and./ts_new.csv
, and the anomaly detection results of the time periodt+1
can be found in./ts_test.csv
.
Please cite our paper if you use this code in your own work:
@article{MengWWYZ21,
title = {Interactive Anomaly Detection in Dynamic Communication Networks},
author = {Xuying Meng and
Yequan Wang and
Suhang Wang and
Di Yao and
Yujun Zhang},
journal = {{IEEE/ACM} Trans. Netw.},
volume = {29},
number = {6},
pages = {2602--2615},
year = {2021}
}