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Automated Website Fingerprinting using Deep Learning (Project for CSE 534 - Fundamentals of Computer Networks)

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Automated Website Fingerprinting using Deep Learning

CSE 534 - Fundamentals of Computer Networks

Reference Paper

Rimmer, V., Preuveneers, D., Juarez, M., Goethem, T. V., & Joosen, W. (2018). Automated website fingerprinting through Deep Learning. Proceedings 2018 Network and Distributed System Security Symposium. https://doi.org/10.14722/ndss.2018.23105

Webpage by the authors of the above paper

https://distrinet.cs.kuleuven.be/software/tor-wf-dl/
Repository: https://github.com/DistriNet/DLWF

Dataset

For our implementation, we have used the Closed World dataset of 100 websites consisting of 2500 traces each.
The dataset can be downloaded from https://distrinet.cs.kuleuven.be/software/tor-wf-dl/files/tor_100w_2500tr.npz.

Once the dataset is download, unzip the .npz file and copy the extracted files (data.npy and labels.npy) in the ./data/ folder.

Contributors

Jimit Dholakia - jimit105
Yasharth Sharma - Yasharthsh
Sai Manikanta Avula - SaiManikantaAvula

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Automated Website Fingerprinting using Deep Learning (Project for CSE 534 - Fundamentals of Computer Networks)


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Language:Jupyter Notebook 77.3%Language:Python 22.7%