Phishing URL Detection using Python and ML

Project Overview:

• Feature Engineering:Engineered relevant features from URL characteristics to enhance the model’s ability to discern between fake and real URLs.
• Decision Tree Model Construction: Designed and implemented a decision tree model that iterates through various criteria to identify patterns indicative of phishing URLs.
• Model Evaluation: Evaluated the model’s performance using accuracy metrics, achieving an impressive 96% accuracy score in distinguishing between phishing and legitimate URLs.

Through this project, I showcased my proficiency in applying machine learning techniques to address real-world cybersecurity challenges. The developed decision tree model serves as a valuable tool in the ongoing battle against phishing attacks, providing users with an additional layer of defense against online threats. Moving forward, further enhancements and refinements to the model could potentially bolster its performance and contribute to the continuous improvement of cybersecurity practices.