Skip to content

websitefingerprinting/WFZoo

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

40 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

WFZoo: A Toolbox for SOTA Website Fingerprinting Attacks and Defenses

Since my previous toolbox is not well organized and out-of-date (written in keras and py37), I decide to rewrite it. This toolbox is still under development. I will add more attacks and defenses in the future. I tested the code under both Python 3.8 and Python 3.11. The conda environment I provided is based on Python 3.8 with pytorch 2.0 and cuda 11.

TODO List

  • About attacks
    • DF attack
    • Tik-Tok attack
    • RF attack
    • Add more attacks
    • Implement Pytorch amp mode
  • About defenses
    • FRONT
    • Tamaraw
    • RegulaTor (I barely tried to optimize the author's code)
    • WTF-PAD (I did make some effort to clean up the code. Only norm_rcv is implemented. Still a lot of for loops. Do not have time to rewrite everything :( )

How to use

1. Install dependencies

conda env create -f py38.yaml
conda activate py38

2. Dataset Format

It has been a convention to name a trace as "A-B.cell" or "C.cell". Here, A is the class number of the trace, B is the instance number of the trace. "C.cell" is the C-th non-monitored trace in the dataset.

3. Train and Test an Attack

python run_attack.py  --attack df --data-path ~/somedataset/ \
--mon-classes 100 --mon-inst 100 --unmon-inst 10000 \
--open-world

This command will perform a 10-cross-validation attack on the given dataset.

--attack specifies the attack to evaluate (currently support DF and Tik-Tok).

--data-path specifies the path of the dataset.

--mon-classes specifies the number of monitored classes.

--mon-inst specifies the number of monitored instances per class.

--unmon-inst specifies the number of unmonitored instances.

--open-world makes an open-world evaluation (by default: closed-world evaluation)

--one-fold only run one fold instead of 10 cross validation.

--suffix specifies the suffix of each file in the dataset (By default: .cell). Change it if your dataset is not end with .cell.

4. Simulate a Defense

python run_defense.py --defense front --data-path ~/somedataset/ \
--config-path ./defenses/config/front.ini \
--mon-classes 100 --mon-inst 100 --unmon-inst 10000 --open-world

About

Aim to reimplement the state-of-the-art attacks and defenses

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages