# SCAred
[](https://gitlab.com/eshard/scared/commits/master)
[](https://pypi.org/project/scared/)
[](https://anaconda.org/eshard/scared)
[](https://anaconda.org/eshard/scared)
scared is a side-channel analysis framework.
## Getting started
### Prerequisites
You will need **Python 3.6+** to use and install scared. You can use pip (or any pip based tool like pipenv) or conda to install it.
### Installation
To install scared, you can use pip (or pipenv, or any other pip based-tool) or conda:
```bash
$ pip install scared
# or with Conda
$ conda install -c eshard scared
```
### Make a first cool thing
Start using scared by doing a cool thing:
```python
# First import the lib
import scared
# Define a selection function
@scared.attack_selection_function
def first_add_key(plaintext, guesses):
res = np.empty((plaintext.shape[0], len(guesses), plaintext.shape[1]), dtype='uint8')
for i, guess in enumerate(guesses):
res[:, i, :] = np.bitwise_xor(plaintext, guess)
return res
# Create an analysis CPA
a = scared.CPAAttack(
selection_function=first_add_key,
model=scared.HammingWeight(),
discriminant=scared.maxabs)
# Load some traces, for example a dpa v2 subset
ths = scared.traces.read_ths_from_ets('dpa_v2.ets')
# Create a container for your ths
container = scared.Container(ths)
# Run!
a.run(container)
```
## Documentation
To go further and learn all about scared, please go to [the full documentation](https://eshard.gitlab.io/scared).
## Contributing
All contributions, starting with feedbacks, are welcomed.
Please read [CONTRIBUTING.md](CONTRIBUTING.md) if you wish to contribute to the project.
## License
This library is licensed under LGPL V3 license. See the [LICENSE](LICENSE) file for details.
It is mainly intended for non-commercial use, by academics, students or professional willing to learn the basics of side-channel analysis.
If you wish to use this library in a commercial or industrial context, eshard provides commercial licenses under fees. Contact us!
## Authors
See [AUTHORS](AUTHORS.md) for the list of contributors to the project.
scared-0.7.3.tar.gz （66个子文件） 
scared-0.7.3 
MANIFEST.in 27B PKG-INFO 4KB tests preprocesses test_preprocesses_absolute_difference_combination.py 5KB test_preprocesses_centered_product.py 5KB test_preprocesses_simple.py 4KB test_preprocesses_timefreq.py 9KB __init__.py 0B test_preprocess_decorator.py 3KB test_preprocesses_product_combination.py 5KB test_preprocesses_difference_combination.py 5KB end_to_end test_xe2e_mia.py 807B test_e2e_anova.py 644B __init__.py 0B test_e2e_nicv.py 642B test_e2e_snr.py 762B test_e2e_cpa.py 632B test_e2e_dpa.py 1KB distinguishers test_partitioned_distinguishers.py 13KB test_distinguishers.py 9KB __init__.py 0B setup.cfg 1KB scared preprocesses high_order _base.py 3KB time_freq.py 8KB __init__.py 189B standard.py 7KB _base.py 2KB __init__.py 230B first_order.py 4KB models.py 7KB discriminants.py 3KB aes selection_functions encrypt.py 6KB __init__.py 45B decrypt.py 3KB __init__.py 88B base.py 32KB selection_functions __init__.py 50B base.py 7KB des selection_functions encrypt.py 9KB __init__.py 45B decrypt.py 5KB __init__.py 88B base.py 41KB __init__.py 2KB container.py 6KB analysis template.py 7KB __init__.py 440B _analysis.py 3KB base.py 11KB distinguishers template.py 4KB partitioned.py 8KB mia.py 4KB __init__.py 823B dpa.py 3KB cpa.py 4KB base.py 5KB ttest.py 5KB _utils.py 328B __version__.py 102B setup.py 525B scared.egg-info PKG-INFO 4KB
requires.txt 33B not-zip-safe 1B SOURCES.txt 2KB top_level.txt 13B dependency_links.txt 1B README.md 2KB资源评论
