AI-Fraud Website Detection System

Abstract

The rise of digital transactions and online services has increased the number of fraudulent websites that deceive users into sharing sensitive data such as login credentials, bank details, and personal information. This paper presents an AI-based Fraud Website Detection System that automatically identifies and classifies websites as legitimate or fraudulent using machine learning algorithms. The proposed model analyzes website features such as URL structure, domain information, SSL certification, and page content. A dataset of labeled URLs was used to train and test the model, achieving high accuracy in detecting phishing and scam websites. The system can be integrated with browsers or cybersecurity tools to provide real-time protection to users.