https://github.com/giorgiosld/machine-learning-in-cybersecurity

This repository contains the coursework and projects for the Machine Learning in Cybersecurity (T-710-MLCS) course supplied in the Cybersecurity Master Degree at Reykjavik University.
https://github.com/giorgiosld/machine-learning-in-cybersecurity

adversarial-machine-learning cybersecurity machine-learning machine-learning-cyber-security ml-cybersecurity

Last synced: about 1 month ago
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This repository contains the coursework and projects for the Machine Learning in Cybersecurity (T-710-MLCS) course supplied in the Cybersecurity Master Degree at Reykjavik University.

• Host: GitHub
• URL: https://github.com/giorgiosld/machine-learning-in-cybersecurity
• Owner: giorgiosld
• License: mit
• Created: 2024-08-23T09:21:37.000Z (4 months ago)
• Default Branch: main
• Last Pushed: 2024-10-21T18:09:09.000Z (2 months ago)
• Last Synced: 2024-10-22T12:35:55.010Z (2 months ago)
• Topics: adversarial-machine-learning, cybersecurity, machine-learning, machine-learning-cyber-security, ml-cybersecurity
• Language: Python
• Homepage:
• Size: 77.7 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Machine Learning in Cybersecurity

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.

## Repository Structure

The repository is organized according to the key topics explored during the "Machine Learning in Cybersecurity" course:

- [Bank Fraud Detection](bank_fraud/): This directory contains the code and resources related to the bank fraud

detection topic.

- [Spam Detection](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](network_intrusion_detection/): This directory contains the code and resources for the network intrusion detection topic.

- [Malware Classification](malware_classification/): This directory contains the code and resources for the malware classification topic.

- [Adversarial Machine Learning](adversarial_machine_learning/): This directory contains the code and resources for the adversarial machine learning topic.

## Prerequisites

- Python 3.x;

- virtualenv;

- Specific libraries mentioned in the `requirements.txt` file;

## Setup

1. Clone the repository;

    ```

    git clone https://github.com/giorgiosld/Machine-Learning-in-Cybersecurity.git

    cd Machine-Learning-in-Cybersecurity

    ```

2. Create and activate virtual environment;

    ```

    virtualenv venv

    source venv/bin/activate

    ```

3. Install the required libraries;

    ```

    pip install -r requirements.txt

    ```

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.