Secure ML Library

An open-source library for security evaluation of machine learning (ML)-based algorithms

Secure ML Research   Tutorial: Wild Patterns   Secure ML Library   Web Demo
Secure ML Library (SecML-Lib) is an open-source Python library implementing poisoning and evasion attacks against a wide family of learning algorithms, including SVMs, Neural Nets, Random Forests, and other algorithms available from scikit-learn. SecML-Lib also implements some of the secure-learning techniques developed by our team in the past years.
Stay in touch, SecML-Lib will be released soon!


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