Malicious URL Classifier

This is the project for the Artificial Intelligence for Cybersecurity course of the University of Pisa.

Table of Contents

• Project Structure
• Prerequisites
• Running the Application
• Stopping the Application
• License

Project Structure

The repository is organized as follows:

malicious-url-classifier/
├── app/
├── datasets/
│ ├── kaggle.csv
│ └── dataset.csv
├── Dockerfile
├── docker-compose.yml
├── Malicious_URL.ipynb
├── decision_tree.svg
├── Presentation.pdf
└── README.md

Folder Descriptions

• app/: Contains the sample application code and its dependencies.
• datasets/: Contains the datasets used for this project.
  • kaggle.csv: the initial raw dataset for the benign URLs.
  • dataset.csv: the final dataset obtained after the feature extraction process.
• Dockerfile: Dockerfile for the sample application.
• docker-compose.yml: Docker Compose configuration file.
• Malicious_URL.ipynb: Jupyter Notebook of the project.
• decision_tree.svg: An image of the final decision tree extracted.
• Presentation.pdf: The presentation used for this project.
• README.md: This document.

Prerequisites

Before running the application, ensure you have the following installed:

• Docker
• Docker Compose

Running the Application

1. Clone the repository:

   git clone https://github.com/gabrielepongelli/malicious-url-classifier.git
   cd malicious-url-classifier

2. Build and run the containers:

   docker compose up --build

   This command will build the Docker images and start the containers as defined in the docker-compose.yml file.

3. Access the application:

   The application will be available at http://localhost:5000.

Stopping the Application

To stop the application and remove the containers, run:

docker compose down

This command stops and removes all the containers defined in the docker-compose.yml file.

License

This project is licensed under the MIT License - see the LICENSE file for details.