SecuML - Machine Learning for Computer Security

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SecuML is a Python tool that aims to foster the use of Machine Learning in Computer Security. It is distributed under the GPL2+ license. It allows security experts to train detection models easily and comes with a web user interface to visualize the results and interact with the models. SecuML can be applied to any detection problem. It requires as input numerical features representing each instance. It supports binary labels (malicious vs. benign) and categorical labels which represent families of malicious or benign behaviours.

https://anssi-fr.github.io/SecuML
https://github.com/ANSSI-FR/SecuML

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