Estimate and prevention of malicious URL using logistic regression ML techniques
Nagendar Yamsani, K. Sarada, Mohammed Abbas Ahmed, K. Saikumar · AIP conference proceedings · 2024
URLs that are easily recognizable by humans are used to identify the billions of websites and servers that make up the modern internet.Malicious URLs may be used by the opposing to get unauthorized access to classified material and then presented to the user as a URL.Malicious URLs are URLs that allow for unwanted activities to be taken without the user's permission.It's critical to verify URLs in order to ensure that users can't be prevented from engaging in unethical activity like stealing private and classified data or installing malware that's tailored to the methods being used, and this results in massive losses every year around the globe.SVM, a machine learning technique, may be used to identify fraudulent URLs.One of the most important aspects of a device is to allow the URLs requested by the customer and block the dangerous URLs before they reach the user.In order to identify harmful URLs, blacklisting is one of the simplest and most straightforward methods.