Malware Discovery with Machine Learning

This is a repository for a university project on the "Cybersecurity, Reliability and Risk Lab" module. It aims malware discovery with chosen algorithms, like K-Nearest Neighbors, Decision Tree or Naive Bayes.

Description

Project implementation is held with python 3.8. Three simple Machine Algorithms are used for comparison: KNN, Decision Tree and Naive Bayes. Data to fed and teach algorithms is a CSV file with 56 features and label a colum. The repository includes a Jupyter Notebook with code snippets and its description.

Prerequisites

A couple of non-standard python libraries are used. To install them, use the following command:

pip install -r requirements.txt

Authors

• Kamil Kaliś kamkali – KNN
• Jakub Burghardt davex98 – Decision Tree
• Michał Szczepaniak-Krupowski MichSzczep – Naive Bayes