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DeepMalwareDetector

A Deep Learning framework that analyses Windows PE files to detect malicious Softwares. the project includes:

  • Sate of the art of the work done using machine learning or deep learning.
  • A new approach for detection:
    • Enhancing detection rate and reducing False positive rate
    • Proposing a technique to garantee the evolution of the model
  • Defining and implementing a framework to extract PE files representation, this includes:
    • PE headers
    • PE strings
    • Opcodes sequences
    • Opcodes stats
    • Bytes n-grams
    • API Calls
  • Building a training data set
    • Over 120.000 malwares
    • Over 30.000 benign software
  • Defining and implementing a Deep Learning architecture to learn on the extracted data
    • SAE: n-grams of bytes
    • RNN: sequences of opcodes
    • CNN: exe to bytes image
    • FNN: a submodule to the SAE

Languages

Python90.5%HTML4.9%CSS1.5%SCSS1.2%C1.2%Jupyter Notebook0.3%JavaScript0.2%PowerShell0.1%Fortran0.0%Cython0.0%Smarty0.0%Batchfile0.0%Procfile0.0%

Contributors

Latest Release

v1April 17, 2023
Created February 14, 2020
Updated February 21, 2026
islem-esi/DeepMalwareDetector | GitHunt