Getting Started

The code has been developed for this challenge and is available on Github in two version: Pytorch repo and Tensorflow repo.

Although, the repositories are using neural network, there are restriction in the use of template attack or stochastic attack.

Installing dependencies:

The framework runs with python >= 3.8 and python <= 3.11. Futhermore, it requires the following dependencies:

• venv , part of python's standard library, but not included in some python installations

(e.g., run apt install python3-venv to obtain it)

• pip for most of the python installations (on Ubuntu, apt install python3-pip)

We highly recommend using a UNIX environment (on Windows, use WSL)

Cloning repo

First, one can clone the challenge repository.

For Pytorch:

git clone https://github.com/pace-tl-ntu/ches2025_pytorch

For Tensorflow:

git clone https://github.com/pace-tl-ntu/ches2025_tf.git

Downloading the datasets

See Datasets page for downloading the datasets.

Train models during the profiling phase

In the following, we use ./../Datasets as the path to where the dataset is stored, and ches_2025 as the directory of the repository.

For PyTorch, one should go https://pytorch.org/ to install the pytorch version: 2.7.0

For TensorFlow, make sure that the tensorflow version: 2.19.0

cd ches_2025
python3 -m venv ches_env
source ches_env/bin/activate
pip install pip --upgrade 
pip install -r requirements.txt

#For Pytorch library, go to https://pytorch.org/
#and install pytorch before running the following command line. 

python3 main_{tf/pytorch}.py #Train Neural Network
deactivate

*For MacOS, please use Pytorch instead of Tensorflow.

Analyze the trained model during the attack phase

For submission, one should edit the code analyze_{tf/pytorch}.py, where they have to load their model to run the function evaluate() to compute the guessing entropy. There are some code there

python3 analyze_{tf/pytorch}.py

The function evaluate() will output something like:

GE [118. 132.99 133.72 137.16 130.53 127. 132.64 131.46 130.2 131.53
135.33 135.04 137.32 138.76 133.96 134.03 135.71 134.04 134.74 137.19
138.68 136.61 136.55 134.75 136.74 137.48 134.59 131.45 132.92 134.83
135.36 134.8 134.29 132.21 132.17 132.22 132.37 131.61 131.63 131.09
131.65 132.17 132.68 132.13 131.18 130.95 130.26 129.85 132.93 133.7
136.28 136.87 138. 137.15 136.42 134.62 135.46 134.45 134.58 134.5
135.64 135.27 134.65 135.73 134.99 135.77 136.71 136.5 136.07 135.33
135.38 136.12 135.65 135.43 133.96 133.75 136.19 138.79 137.45 136.79
137.65 136.69 138.11 138.98 138.11 138.13 137.8 138.46 138.3 137.25
136.35 137.59 137.04 136.75 137.76 138.82 139.51 140.16 139.02 139.83]
NTGE inf

If there are any issues, please reach out to the organizer.