ADVANCED PHISHING LINK DETECTION AND PREVENTION SYSTEM

The phishing link detection system is most common attack on the cybercrime and more on the modern internet.it has become the most severe and dangerous cybercrime on the internet.More studies have collected their work on the precaution, identification, and on phishing attacks; however, there is no complete solution for attacks.Therefore, machine learning plays an important role in defending against cybercrimes involving phishing attacks.The study is based on the phishing URL-based dataset extracted from the different dataset repository, which consists of phishing and legitimate URL attribute.This study uses machine learning models such as Random Forest, XGBoost, Support Vector Machine and Decision Trees.Recent literature and author observations provide practical evidence supporting the effectiveness of ensemble and deep-learning models in phishing link detection system.The objective was to detect phishing URLs and evaluate the effectiveness of various machine learning techniques by comparing their accuracy rates.In this, proposed methodology four datasets were used i.e.Phishing, URL, Email and SMS.