This repo contains the assignments, works and project made during the Course Machine Learning in Cybersecurity taken in Reykjavík University during the Fall Semester 2024. The objective of this repository is to explore and implement various machine learning algorithms to address common cybersecurity challenges such as spam detection, bank fraud detection and more.
The repository is organized according to the key topics explored during the "Machine Learning in Cybersecurity" course:
- Bank Fraud Detection: This directory contains the code and resources related to the bank fraud detection topic.
- Spam Detection: This directory contains the code and resources for the spam detection topic, which was addressed in the first assignment of the course.
- Network Intrusion Detection: This directory contains the code and resources for the network intrusion detection topic.
- Malware Classification: This directory contains the code and resources for the malware classification topic.
- Adversarial Machine Learning: This directory contains the code and resources for the adversarial machine learning topic.
- Python 3.x;
- virtualenv;
- Specific libraries mentioned in the
requirements.txtfile;
- Clone the repository;
git clone https://github.com/giorgiosld/Machine-Learning-in-Cybersecurity.git cd Machine-Learning-in-Cybersecurity - Create and activate virtual environment;
virtualenv venv source venv/bin/activate - Install the required libraries;
pip install -r requirements.txt
This project is licensed under the MIT License - see the LICENSE file for details.