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a.i.-exploiting/bra.i.nsmasher-presentation/Hybrid_Malware_Classifier_Part_1.md

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+#A.I. HYBRID MALWARE CLASSIFIER
+##INTERMEDIATE PYTHON SKILL, INTERMEDIATE MACHINE LEARNING SKILLS (Part 1)
+
+In this series of notebook we are going to build an **hybrid malware classifier.**
+
+For the **First part** we will focus on the scripting that involves dynamic analysis. Any steps of this series will come useful in order to detect malwares, and in this piece we will try to classify them based on their behaviour, utilizing the logs produced by running a program.
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+In the **Second Part** we will see how to manipulate the logs files in order to add robustness to our classifier and adjust the code to counter the more advanced methods of A.I. Malware Evasion.
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+In the **Third Part** we will create a Static Malware Classifier.
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+For the **Fourth Part** For the Fourth Part we will add some tactics to add robustness to our Static classifier and merge the latter with our Dynamic Classifier.
+
+**PLEASE NOTE:** This Series strongly relies on building a dataset on your own, even if it's not mandatory.<br>
+There are also many available datasets for Static and/ or Dynamic Malware analysis on several sites for this type of classification, like Ember, VirusShare, Sorel-20M, but i strongly encourage that you build one or your own.
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+Here's the link to our [**colab notebook**](https://colab.research.google.com/drive/1nNZLMogXF-iq-_78IvGTd-c89_C82AB8#scrollTo=lUHLMl8Pusrn) enjoy and stay safe :)
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