DLWF

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This is the source code used for the research paper Automated Website Fingerprinting through Deep Learning:

https://tor-wf-dl.distrinet-research.be/

The code is currently not maintained, email us for updates: [email protected]

If you found our framework or data useful for your research, please cite:

@inproceedings{Rimmer2018,
  title={Automated Website Fingerprinting through Deep Learning},
  author={Rimmer, Vera and Preuveneers, Davy and Juarez, Marc and Van Goethem, Tom and Joosen, Wouter},
  booktitle={Proceedings of the 25nd Network and Distributed System Security Symposium (NDSS 2018)},
  year={2018},
  organization={Internet Society}
}

The datasets used for the evaluation are available to download under these links:

Closed World --

https://tor-wf-dl.distrinet-research.be/files/tor_100w_2500tr.npz

https://tor-wf-dl.distrinet-research.be/files/tor_200w_2500tr.npz

https://tor-wf-dl.distrinet-research.be/files/tor_500w_2500tr.npz

https://tor-wf-dl.distrinet-research.be/files/tor_900w_2500tr.npz

Open World --

https://tor-wf-dl.distrinet-research.be/files/tor_open_200w_2000tr.npz

https://tor-wf-dl.distrinet-research.be/files/tor_open_400000w.npz

Concept drift --

https://tor-wf-dl.distrinet-research.be/files/tor_time_test3d_200w_100tr.npz

https://tor-wf-dl.distrinet-research.be/files/tor_time_test10d_200w_100tr.npz

https://tor-wf-dl.distrinet-research.be/files/tor_time_test2w_200w_100tr.npz

https://tor-wf-dl.distrinet-research.be/files/tor_time_test4w_200w_100tr.npz

https://tor-wf-dl.distrinet-research.be/files/tor_time_test6w_200w_100tr.npz