Detection of Phishing Website Using ML

Phishing websites pose a severe threat to cyber security, tricking users into divulging sensitive information. This
research introduces the framework for machine learning, to accurately detect phishing websites. The proposed system
utilizes the Random Forest algorithm, and NLP tools such as Word Cloud and NLTK for feature extraction and
visualization. Python libraries like SK learn and pandas are used for prepossessing and model evaluation. The results
indicate that Logistic Regression achieves an accuracy of around 90%, making it a robust solution for real-world
phishing detection.