Datasets

Downloading the dataset

There will be only one public datasets given to train the neural networks.

The dataset can be downloaded from the following link.

It consists of 500K profiling traces and 100k attack traces.

The hash of the above dataset is as follows:

132ae2e9a8213c983bf3b63449e9572d5d71d3b376a75b236415d4a728b9379f

There will be three private set of attack traces used for evaluation (see Challenge Rule).

These attack traces will be made public after the challenge ends. The hash of the private datasets (into one file) is as follow:

86ec5b8fefb6ff9aad88112782ea34b6f3785bf9533c94a9ece51ccf9587ca97

Flow of the dataset

The dataset is stored in .h5 file. The flow of the dataset is similar to the ASCAD dataset [1].

The structure of the dataset is outlined as follows:

Dataset

Note: We will be targeting only the first byte for this challenge (i.e. byte $0$).

Loading the dataset

The function to load the dataset can be found in utils.py as the function load_ctf_2025() . This function is used within main_{tf/pytorch}.py and analyze_{tf/pytorch}.py

References

1. Benadjila, R., Prouff, E., Strullu, R. et al. Deep learning for side-channel analysis and introduction to ASCAD database. J Cryptogr Eng 10, 163–188 (2020). https://doi.org/10.1007/s13389-019-00220-8