Web Based Malicious URL Detection Through Feature Selection (Special Characters) with Machine Learning - Anwar Razlan, Rasali (2023)
With the advancement of technology, we see a rise in the advancement of malicious software or malware attacks as well. People should have every right to never fall victim to any of these attacks. This research aims to implement a study of several Machine Learning Algorithms into a web-based malware. This is made possible by feature extraction through a series of codes written in Python. These features will undergo a few specifications before being determined as malicious or benign. The feature extraction process would test output a value in accordance with the URL and determine whether the URL is malicious or otherwise. This research would hopefully be a line of defense to prevent users from coming across to a malware with the help of the proposed project.