Intro

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This repo is the official implementation of An Input-Agnostic Hierarchical Deep Learning Framework for Traffic Fingerprinting (USENIX Security '23). We provide code and datasets here.

It provides a simple but effective method for trace classification.

Requirements

python version >= 3.6

pip install -r requirements.txt

Quick Start

• code:
  list the source codes
• dataset: list the datasets

cd code
python3 main.py

Details see code README.

Citation

@inproceedings{quinput,
  title={An Input-Agnostic Hierarchical Deep Learning Framework for Traffic Fingerprinting},
  author={Qu, Jian and Ma, Xiaobo and Li, Jianfeng and Luo, Xiapu and Xue, Lei and Zhang, Junjie and Li, Zhenhua and Feng, Li and Guan, Xiaohong},
  booktitle={32th USENIX Security Symposium (USENIX Security 23)},
  year={2023}
}

License

This repository is released under the Apache 2.0 license as found in the LICENSE file.

Acknowledgement

Thanks for Tony-Y's implementation of pytorch_warmup.