Malware Detection Using Machine Learning Algorithms

This repository holds all code base and details for the project Malware Classification Using Machine Learning Algorithms submitted in partial fulfilment of my Master's Degree. This repository holds several Jupyter notebooks at several stages/implementations of the project. The consists of the following stages followed through the CRISP-DM methodology:

• 01 - Dataset Loading and Understanding
• 02 - Data Preparation and Feature Importance
• 03 - Modelling and Result Analysis
  • 3.1 - Principal Component Analysis and Random Forest Classification
  • 3.2 - Naive Bayes Classification
  • 3.3 - K-Nearest Neighbour Classification
  • 3.4 - Logistic Regression Classification

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References

A seperate document with all reference links used for this thesis, source code and write up references have all been collated as a seperate document and can be found Here

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