This repository contains an unofficial PyTorch implementations of state-of-the-art deep nerual network based traffic analysis techniques.
Original paper (PDF):
Vera Rimmer, Davy Preuveneers, Marc Juarez, Tom Van Goethem, and Wouter Joosen. Automated Website Fingerprinting through Deep Learning. In 2018 Network and Distributed System Security Symposium (NDSS).
The original AWF website contains 900 websites each with 2500 samples. For the implementation is this repository, we used a subset of this websites with 100 websites and 2500 traces for each of them. You can download the dataset here.
Original paper (PDF)
Payap Sirinam, Mohsen Imani, Marc Juarez, and Matthew Wright. Deep Fingerprinting: Undermining Website Fingerprinting Defenses with Deep Learning. In 2018 ACM SIGSAC Conference on Computer and Communication Security (CCS).
The implementation in this repository is for the closed-world scenarion without any defense mechanisms.
The DF dataset contains 95 websites each with 800 samples for training, 100 samples for validation, and 100 samples for test. You can download the dataset here.
Original paper (PDF)
Sanjit Bhat, David Lu, Albert Kwon, and Srinivas Devadas. Var-CNN: A Data-Efficient Website Fingerprinting Attack Based on Deep Learning. In 2019 Privacy Enhancing Technologies (PETs).
You can find the original dataset of the paper in their repository.
Original paper (PDF)
Payap Sirinam, Nate Mathews, Mohammad Saidur Rahman, and Matthew Wright. Triplet Fingerprinting: More Practical and Portable Website Fingerprinting with N-shot Learning. In 2019 ACM SIGSAC Conference on Computer and Communication Security (CCS).
In this implementation, we use the same dataset as the AWF dataset. This dataset contains 100 websites each with 2500 traces.