Metadata-Version: 2.1
Name: scared
Version: 0.7.6
Summary: scared is a side-channel analysis framework.
Home-page: https://gitlab.com/eshard/scared
Author: eshard
Author-email: scared@eshard.com
License: UNKNOWN
Project-URL: eShard, https://www.eshard.com
Project-URL: Documentation, https://eshard.gitlab.io/scared
Project-URL: Issues, https://gitlab.com/eshard/scared/issues
Description: # SCAred
        
        [![pipeline status](https://gitlab.com/eshard/scared/badges/master/pipeline.svg)](https://gitlab.com/eshard/scared/commits/master)
        [![PyPI version](https://badge.fury.io/py/scared.svg)](https://pypi.org/project/scared/)
        [![Conda installer](https://anaconda.org/eshard/scared/badges/installer/conda.svg)](https://anaconda.org/eshard/scared)
        [![Latest Conda release](https://anaconda.org/eshard/scared/badges/latest_release_date.svg)](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.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.6
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Framework :: Jupyter
Classifier: Framework :: IPython
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Security
Classifier: Topic :: Software Development
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6.0
Description-Content-Type: text/markdown
