The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/21950588

Jaehun Kim; Stjepan Picek; Annelie Heuser; Shivam Bhasin; Hanjalic, A. (Alan) (2023): Preprocessed dataset for the paper "Make some noise. unleashing the power of convolutional neural networks for profiled side-channel analysis". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/21950588.v1

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Categories

• Artificial Intelligence and Image Processing
• Information Systems

Keywords

Convolutional neural networks gaussian noise Machine Learning (ML) Side-channel analysis

Licence

CC BY-NC 4.0

Interoperability

• RO-Crate Metadata

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by Jaehun Kim , Stjepan Picek, Annelie Heuser, Shivam Bhasin, A. (Alan) Hanjalic

Preprocessed dataset for the paper "Make some noise. unleashing the power of convolutional neural networks for profiled side-channel analysis"

This entry contains the preprocessed dataset in NumPy binary format. The dataset is derived from 4 different datasets:

• http://www.dpacontest.org/v4/
• https://github.com/AESHD/AES_HD_Dataset
• https://github.com/ikizhvatov/randomdelays-traces
• https://github.com/ANSSI-FR/ASCAD

The dataset is specifically processed to run the experimental routine provided in the separate repository.

Contributors

Jaehun Kim

Stjepan Picek

Annelie Heuser

Shivam Bhasin

Alan Hanjalic

History

• 2023-01-27 first online, published, posted

Publisher

4TU.ResearchData

Format

*.npy

Associated peer-reviewed publication

Make Some Noise. Unleashing the Power of Convolutional Neural Networks for Profiled Side-channel Analysis

Organizations

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Intelligent Systems