ASCADv2

Description

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.

Dernière mise à jour
24 juillet 2024

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2 discussions

SHA1 values of files to be downloaded.

Posté le 9 juillet 2025
In the original github repo there is a mention or SHA1.txt file at bottom which no longer exists. I still have those files so I am posting here. "author_hashes_type": 'sha1', "author_hashes": { ascadv2-stm32-conso-raw-traces1.h5: "4352910b4f4dea2de872f2122bb530582a238e02", ascadv2-stm32-conso-raw-traces2.h5: "b32a239bbdb3d683833d625a109f17a55d36f24a", ascadv2-stm32-conso-raw-traces3.h5: "10c4cdc37578f8ef6bd59608345548ffd6ba3771", ascadv2-stm32-conso-raw-traces4.h5: "f0aacc9587e94532f86a26355db81e5b4ab2848b", ascadv2-stm32-conso-raw-traces5.h5: "4158149ac9a0bd7a8dda758ddb45927e7015b831", ascadv2-stm32-conso-raw-traces6.h5: "5fd51946c8552514f4c56e8730a0f7cb9ca1ac5e", ascadv2-stm32-conso-raw-traces7.h5: "ab5e6fc117b11aae733ce61c6424f7d55a487039", ascadv2-stm32-conso-raw-traces8.h5: "ef72fb2a388099ef41fbdbb0ccaefc287f048290", ascadv2-extracted.h5: "8de295c8c18d033b13c03474189c0976a49ca993", },

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Posté le 9 février 2021
Could you explain the metadata & labels components like Figure 5 in "Study of Deep Learning Techniques for Side-Channel Analysis and Introduction to ASCAD Database"? I do appreciate your help in advance.