Enhancing Cybersecurity with Machine Learning: Developing a URL Malware Detection System

The increasing use of the internet has made users vulnerable to various cyber threats, particularly malware through URLs. This paper describes a Python-based URL malware detector leveraging machine learning techniques to classify URLs as benign or malicious based on specific features. Models like Logistic Regression and Random Forest have been explored, and performance metrics are discussed to demonstrate the model's accuracy and efficacy.