Machine Learning Strategies to Detect Phishing Website

Recent years have witnessed a substantial increase in website phishing attacks. Many researchers have developed software solutions to detect phishing websites, however it cannot detect these attacks completely. There were several minor challenges in identifying the fraudulent websites. Therefore, the most effective way to detect phishing websites is to incorporate machine learning algorithms into the attack detection process. This improves the overall accuracy of the project and allows for more efficient computation. Implementing machine learning algorithms can also help to overcome the challenges faced by the existing phishing attack detection models. The major purpose of this research is to use the dataset collected to train the ENASSEMBLE Machine Learning (ML) model to detect the phishing websites.