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MalConv-Deep-learning-for-PE-malware-classification

This repository contains the MalConv Architecture trained on EMBER 2018 Dataset to classify the PE file as benign or malware. There are three coding files:

  1. MalConv Training https://github.com/iBibek/MalConv-Deep-learning-for-PE-malware-classification/blob/main/MalConv_Malware_Classification_of_PE_files.ipynb
  2. Model Deployment: https://github.com/iBibek/MalConv-Deep-learning-for-PE-malware-classification/blob/main/Model_Deployment.ipynb
  3. ClientPE File: https://github.com/iBibek/MalConv-Deep-learning-for-PE-malware-classification/blob/main/clientPE.py

The YouTube video is here: https://youtu.be/6Mu3WscWdOo and the report is also in this repo. image

The MalConv architecture is based on the paper https://arxiv.org/pdf/1710.09435.pdf The dataset is from Ember repo: https://github.com/elastic/ember

<iframe width="560" height="315" src="https://www.youtube.com/embed/6Mu3WscWdOo" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>

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