ASCAD (ANSSI SCA Databases) Databases and Neural Networks models, associated to the article "Study of Deep Learning Techniques for Side-Channel Analysis and Introduction to ASCAD Database" available on https://eprint.iacr.org/2018/053.pdf.
Agence Nationale de la Sécurité des Systèmes d'Information
CNN trained model for ASCAD variable key and no desynchronization
ASCAD database version 2. This database contained the power consumption of a STM32 Cortex M4 microcrontroller (STM32F303RCT7) during 800.000 random AES encryptions. The AES encryptions are protected with shuffling and affine masking, and the implementation is available on <https://github.com/ANSSI-FR/SecAESSTM32>. The raw dataset is split into 8 files of 100.000 encryptions, and the extracted dataset contained the 800.000 preprocessed traces with additional metadata. Warning: Due to an acquisition issue, the last trace of each raw file (ascadv2-stm32-conso-raw-traces{1..8}.h5) and the associated metadata are set to zero. Moreover, traces 99999, 199999, 299999, 399999, and 499999 in the profiling part of the file ascadv2-extracted.h5 are also zero. These traces may introduce a bias if used during the evaluation process. In standard usage, the attack part of the ascadv2-extracted.h5 file does not contain any null traces and can be safely used for evaluation. However, we highly suggest to remove all the null traces from the entire dataset.
ASCAD database (raw traces and extracted traces) for ATMega 8515 power consumption of boolean masked AES using a variable key.
CNN trained model for ASCAD variable key and a desynchronization of 50 samples
SCANTRU is a database of EM traces associated to the article "_Security Assessment of NTRU Against Non-Profiled SCA_" presented during the 21st Smart Card Research and Advanced Application Conference (CARDIS 2022).