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Real-Time Scam URL Detection System Using Decision Tree Classifier and TF-IDF Vectorization

1st Dr. T. Amalraj Victorie ,2rd M. Vasuki ,3rd D.Hemasujithaa and 4thR.Keerthana,

1 Professor, Department of computer Applications, Sri Manakula Vinayagar Engineering College (Autonomous), Puducherry

605008, India amalraj@smvec.ac.in

2Associate Professor, Department of computer Applications, Sri Manakula Vinayagar Engineering College (Autonomous), Puducherry 605008, India

dheshna@gmail.com

3Post Graduate student, Department of computer Applications, Sri Manakula Vinayagar Engineering College (Autonomous), Puducherry 605008, India

dhemasujithaa@gmail.com

4Post Graduate student, Department of computer Applications, Sri Manakula Vinayagar Engineering College (Autonomous), Puducherry 605008, India

keerthanaram13@gmail.com

ABSTRACT
The Scam URL Alert System is a web-based application designed to help users determine the legitimacy of URLs by analyzing them for potential threats. The system leverages a machine learning model, specifically a Decision Tree Classifier, to classify URLs as either safe ("legit") or unsafe ("fake").The process begins with the user inputting a URL into the application. Using advanced techniques like tokenization and TF-IDF vectorization, the model extracts features from the URL and predicts its legitimacy. The backend, built with Python's Flask framework, facilitates seamless communication between the user interface and the machine learning model. The system provides an intuitive and dynamic user experience with a visually appealing design, including a custom background image and responsive updates.

Keyword:     URL classification, Phishing prevention , Decision TreeClassifier , TF-IDF vectorization, Cybersecurity, Legitimate URL verification, Sound alert.

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