sbshah97 / hybrid-malicious-code-detection-using-deep-learning

Hybrid Malicious Code Detection using Deep Learning with Keras and Scikit Learn

Hybrid Malicious Code Detection using Deep Learning

About

This is a Keras implementation of A Hybrid Malicious Code Detection Method based on Deep Learning. Basically it is an hybrid model consisting of an autoencoder and a Deep Belief Network.

Details about the dataset are explained at the KDDCup website.

Python Dependencies

• Numpy
• Keras
• Pandas
• Scikit Learn
• Tensorflow

Environment Setup

• It is preferable if you use Python Ananconda Environment. You can download it from here

• Create a new conda environment using the following command:

conda create -n hybrid-code python=3.5

• Activate the environment by running the following code:

source activate hybrid-code

• To install the required libraries, run the following commands:

conda install numpy pandas sklearn

Training

The basic usage is python driver.py.

Contributors

• The Project is created and maintained by Salman Shah.