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A Deep Learning framework that analyses Windows PE files to detect malicious Softwares.

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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