Detecting phishing URL using random forest classifier

Phishing is a threat that targets users by tricking them into revealing sensitive information, such as login credentials, financial data, and personal details. The Random Forest algorithm is a robust and widely used machine learning technique that is used to detect phish URLs.

Key features from URLs are included in the approach. Website-based features include embedded links and redirections. The Random Forest is used to classify URLs as legitimate or phish.

Training and testing the model are done with a labeled dataset of benign URLs. The results show that Random Forest is an effective solution for URL detection. The model's interpretability makes it possible for the identification of the most influential features.

The need for continuous updates to the dataset and features to adapt to evolving techniques is highlighted in this research. Integration of the proposed method into real-time cybersecurity systems is possible.