Reproducibility artifacts for the paper ProvIoT: Detecting Stealthy Attacks in IoT through Federated Edge-Cloud Security.
Folder | Description |
---|---|
data |
Folder containing the data files for IDS execution. |
dco2vec |
Folder containing the code for doc2vec implementation. |
AE |
Folder containing the code for AutoEncoder (AE) execution. |
We will use conda
as the python environment manager. Install the project dependencies from the proviot.yml using this command:
conda env update --name proviot --file proviot.yml
Activate the conda environment before running the experiments by running this command
conda activate proviot
- provIoT.py
- Driver script for ProvIoT, which is an Autoencoder-based IDS that detects anomalous paths.
- Sample causal paragraphs and feature vectors for APT attack available in anomaly-paragraph directory.
Running the ProvIoT script:
python proviot.py
@inproceedings{mukherjee2024acns,
title = {ProvIoT: Detecting Stealthy Attacks in IoT through Federated Edge-Cloud Security},
author = {Kunal Mukherjee and Joshua Wiedemeier and Qi Wang and Junpei Kamimura and John Junghwan Rhee and James Wei and Zhichun Li and Xiao Yu and Lu-An Tang and Jiaping Gui and Kangkook Jee},
year = 2024,
booktitle = {22nd International Conference on Applied Cryptography and Network Security},
series = {ACNS '24}
}