INTELLIGENT URL RISK PREDICTION PHISHING AWARENESS SYSTEM

People are becoming more susceptible to bogus online links that try to steal personal information due to the rapid growth of digital communication.Phishing attacks exploit people's trust by disguising harmful URLs as reliable ones, which can lead to data breaches, identity theft, and financial loss.This study's Intelligent URL Prediction and Phishing Awareness System identifies and evaluates questionable web addresses before a user interacts with them.The system uses data-driven analysis and machine learning techniques to examine the lexical characteristics, domain-based attributes, and structural patterns of URLs.By extracting features including length, special symbols, subdomain usage, redirection patterns, and hosting information, the model determines if a link is safe or harmful.A trained classifier processes these features to produce accurate predictions in real time.In addition to detection, the solution increases awareness by informing users of the danger level through an interactive interface, enabling them to make informed choices.The design incorporates a learning algorithm for classification, pre-processing modules for feature extraction, an intuitive input and feedback interface, and a dataset of genuine and fraudulent links.The model is regularly enhanced through training and validation, ensuring dependability and adaptability to evolving attack strategies.Web technologies are employed for the interface and display, while Python is used for backend processing in the system design.This research contributes to cyber security by offering a protection that lessens user sensitivity to deceptive links.In addition to teaching people how to anticipate risks, it also teaches them safe browsing techniques.The recommended strategy promotes safe internet use, increases awareness, and enhances online protection in both personal and professional contexts.Because the system was designed with scalability and flexibility in mind, it may easily be connected to email clients, browsers, or organizational security systems for broader protection.By maintaining logs of user interactions and studied URLs, it makes continuous monitoring and prediction accuracy improvement easier.The awareness component assists users in improving their cyber security practices by alerting them to potential threats and providing guidance on identifying questionable links.Because the system combines intelligence prediction with educational help, it provides a proactive and practical solution to reduce the risks of phishing in everyday internet use.