A phishing website detection system based on machine learning methods
Chengge Duan · Academic Journal of Computing & Information Science · 2023
In today's Internet age, phishing attacks are a common means of cyberattacks. Most existing URL-based anti-phishing technologies are simple and effective, but lagging, while machine learning and deep learning-based approaches can effectively improve detection efficiency. This study advocates the use of TF-IDF for website data preprocessing followed by a random forest model to achieve phishing website feature classification. The final experimental results show that the model accuracy of the random forest algorithm based on machine learning to judge phishing websites is high and the anti-phishing capability is superior.