Python库 | scared-0.7.3.tar.gz

# 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.