This project was completed for one of my cybersecurity-related coursework assignments. The focus was phishing URL detection using machine learning. I worked with the PhiUSIIL Phishing URL Dataset for this assignment, which contains a large number of URLs that are labeled as either phishing or legitimate. The goal was to train multiple machine learning models to predict whether or not a URL was suspicious or safe, based on the different features. This project stood out to me because it felt connected to a real security problem.

Skills and Values Developed

This project directly helped me evolve multiple skills, such as analytical thinking, problem solving and working with technical data. I was required to compare several learning models, understand how the dataset was structured, and think about which metrics mattered the most when measuring performance. As someone aspiring to work in cybersecurity, this project was very helpful because it showed how technical tools such as machine learning can be used to help detect threats and improve security.

Artifact Inventory

• Project report
• Python code file
• Model evaluation results

Featured Artifact

The main artifacts I would like to include on this page are the written project report and the Python code itself. The report explains the purpose of the project, the dataset, the machine learning models I used, and the final results. These artifacts help someone who does not know me or the course understand both the technical side of the project and why it matters in a cybersecurity context.