Welcome!

This site serves as a demonstration of my Bachelor's Thesis project focused on Intrusion Detection Systems (IDS). It showcases the testing and comparison of Isolation Forest and Autoencoder algorithms on the popular CICIDS dataset.

What is this project about?

The goal of this demo is to demonstrate how machine learning models can be used to:

• Detect anomalies in network traffic
• Identify potential cybersecurity threats
• Process and analyze datasets in real time
• Provide a modern and clear visual output

What algorithms are included?

• Isolation Forest – anomaly detection based on random isolation
• Autoencoder – neural network that reconstructs normal traffic and flags anomalies

What can you do here?

• Upload your own dataset and test the algorithms
• Run default tests on the CICIDS dataset

This demo is for educational and research purposes only!