Dataset

For each target, we have acquired 3 datasets:

training dataset,
validation dataset,
test dataset.

The training and validation datasets are public, while the test dataset is used to evaluate the submissions and kept private by the organizers.

All datasets correspond to a correct usage of the SMAesH core: for each trace, the sharing of the key and of the plaintext is fresh. Moreover, we reseed the core before each trace with a fresh seed (the reseeding is not included in the trace). In the training dataset we use a fresh random key and a fresh random plaintext for each trace. The validation and test datasets are sampled identically and use a single fixed key (sampled at random) for the whole dataset, and a fresh random plaintext for each trace.

Dataset versions

v1 is the dataset used for the CHES 2023 SMAesH challenge. The fk1 part of that dataset is kept private.
v2 contains the same data as the v1 dataset, under a file structure more suitable for archival. All the parts of this dataset are public, including fk1.

Dataset parameters

The dataset contains the power measurements collected with the evalutation setups described in Targets together with input data used at each execution of the core execution. In particular, the following fields can be found:

Label	Type	Length	Description
traces	int16	ns	power traces measurement of ns time samples.
umsk_plaintext	uint8	16	unshared plaintext.
umsk_key	uint8	16	unshared key.
msk_plaintext	uint8	16 \( \cdot \) d	plaintext sharing with d shares.
msk_key	uint8	16 \( \cdot \) d	key sharing with d shares.
seed	uint8	10	PRNG seed of 80 bits.

The datasets have different levels of granularity in terms of data they contain. The following table summarizes which fields are provided with each datasets for all targets:

	Training / Validation (A7_d2)	Training / Validation (S6_d2)	Test
traces	☑	☑	☑
umsk_plaintext	☑	☑	☑
umsk_key	☑	☑
msk_plaintext	☑
msk_key	☑
seed	☑

Finally, the next table summarizes the global size of each dataset (in term of amount of traces).

Dataset name	Target	Role	Number of traces	Length of traces
`SMAesH-A7_d2-vk0`	Artix-7 (\( d = 2 \))	profiling	\( 2 ^ {24} \)	\( 4250 \)
`SMAesH-A7_d2-fk0`	Artix-7 (\( d = 2 \))	validation	\( 2 ^ {24} \)	\( 4250 \)
`SMAesH-A7_d2-fk1`	Artix-7 (\( d = 2 \))	test	\( 2 ^ {24} \)	\( 4250 \)
`SMAesH-S6_d2-vk0`	Spartan-6 (\( d = 2 \))	profiling	\( 2 ^ {24} \)	\( 4400 \)
`SMAesH-S6_d2-fk0`	Spartan-6 (\( d = 2 \))	validation	\( 2 ^ {24} \)	\( 4400 \)
`SMAesH-S6_d2-fk1`	Spartan-6 (\( d = 2 \))	test	\( 2 ^ {24} \)	\( 4400 \)

Files organization and dataset reading

The dataset for the SMAesH challenge is composed of several datasets, which are grouped by target and by security order (denoted as a target isntance). For each target instance, we provide the training and the validation dataset (respectively vk0 and fk0), and keep private the test dataset (fk1). Each dataset is described by a manifest file (denoted manifest.json) that describes the content of the dataset (including a file list and a way to check integrity) and is composed of several sub-directories (one per field stored in the dataset which is containing the fields data). The data files use the NPY format.

The dataset are expected to be read with the tool provided in dataset.py specifically implemented for this purpose. It provides top level functions that allows to load the data contained in a dataset per blocks of arbitrary size (see the definition of iter_ntraces in dataset.py and its usage in demo_submission/attack.py for more details).

The architecture convention described above will be followed when the SMAesH dataset will be extended with new target cases. The dataset organisation for the different targets are depicted by the following trees

smaesh-dataset/
+-- smaesh-dataset-A7_d2-vk0/
| + manifest.json
| +-- traces/
| +-- umsk_plaintext/
| +-- umsk_key/
| +-- msk_plaintext/
| +-- msk_key/
| +-- seed/
+-- smaesh-dataset-A7_d2-fk0/
| [...]
+-- smaesh-dataset-A7_d2-fk1/
| [...]
+-- smaesh-dataset-S6_d2-vk0/
| [...]
+-- smaesh-dataset-S6_d2-fk0/
| [...]
+-- smaesh-dataset-S6_d2-fk1/
| [...]

Hashes of datasets

SHA256 hashes of manifest.json files (dataset v1):

e067944fa0c630301c29f09cb53747bafd148af29032c87ff3a20a07e6401bc6 A7_d2-vk0/manifest.json
91db2ed958c7c00e07eaec07cec8818e30c0dfd79cfcb8bac856db41f5b485b9 A7_d2-fk0/manifest.json
08690d4152c2c6b979bd20cad489b5c99dafac7ad970fb60bcf91d67ea44be12 A7_d2-fk1/manifest.json
6af82b2c13eec7de974f3ec25756c470910c4aeca612988bad7d5bcb39a74f7a S6_d2-vk0/manifest.json
fd0469d839336f0f7fe644c97949c1dfee9eb145011213b3ef29b4e334c5753b S6_d2-fk0/manifest.json
90f2b82fc3ec788523e90ef9682864dd3682179d7b5f19f8439a583cc87eb5fe S6_d2-fk1/manifest.json

SHA256 hashes of manifest.json files (dataset v2):

6045582ea4de5545682579d08acc57b5c0f1ea4e73e898f5ca0128af643305a1  smaesh-dataset-A7_d2-fk0/manifest.json
52823b9d7ee325a7e1f257c3b23b3f9fb9a911f517c1169b3118ee81f5740855  smaesh-dataset-A7_d2-fk1/manifest.json
f7aef1456ce193ed2823dc0ba7c5dbe6b0c84cf6868ac8bdffcb60cea0e519cf  smaesh-dataset-A7_d2-vk0/manifest.json
c0d6ead05f9d5cad80bde5360b2c89d7686164afd0c775adac887095c080b307  smaesh-dataset-S6_d2-fk0/manifest.json
b90de1d3c9e040303ffaf44f44c713947da2fdeae53aca768f3397c5ef295990  smaesh-dataset-S6_d2-fk1/manifest.json
36ad6916dd5b4bd6c09c1152123d26c196721c82c68135dba5979b30384f8199  smaesh-dataset-S6_d2-vk0/manifest.json

Dataset download

The v2 dataset is available here. The v1 dataset is not publicly available anymore.

SHA256 hashes of the compressed files:

ea1d2f58939708c617f02040350c5d125ad78808c49e8dbb7f0790cd2a3d1c77  smaesh-dataset-A7_d2-fk0.tar.zstd
7ed17c5e08fb76d59e304ee1320f2acc10783da27b9d4ed8b3295f22944055a4  smaesh-dataset-A7_d2-fk1.tar.zstd
f8edcc26fbed4c6f96ccb7fbd34b7f12a2b8b4abb515c1eb5c949c88526ab9b5  smaesh-dataset-A7_d2-vk0.tar.zstd
1ad75f3b2f0a037711ea49ef0ad61a6d20d04e0c6b9f0a1a4697288420e314cf  smaesh-dataset-S6_d2-fk0.tar.zstd
a2f22abc9beffbae87e2970eccd8f345cf755c1eb2a8af9d37120f85d58d8a3d  smaesh-dataset-S6_d2-fk1.tar.zstd
deae6c33f6d5af04f91043eafbe21617eec895121f99c480e471ce3363c9afb6  smaesh-dataset-S6_d2-vk0.tar.zstd

The files are compressed with the zstd tool (typically available on linux distributions as the zstd package), and archived in the tar format.

Example decompression command:

zstdcat -T0 smaesh-dataset-A7_d2-vk0.tar.zstd | tar xv