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Code and data for the paper _ProvIoT: Detecting Stealthy Attacks in IoT through Federated Edge-Cloud Security__.

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ProvIoT: Detecting Stealthy Attacks in IoT through Federated Edge-Cloud Security

Reproducibility artifacts for the paper ProvIoT: Detecting Stealthy Attacks in IoT through Federated Edge-Cloud Security.

Folder structure

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.

Environment Setup

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

  • 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

Citing us

@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}
}

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Code and data for the paper _ProvIoT: Detecting Stealthy Attacks in IoT through Federated Edge-Cloud Security__.

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