Naive bayes algoritmasını kullanarak kötü amaçlı yazılım url'sini algılama

Hacking and fake pages are the basis of problems and suspicious activities on the Internet, Therefore, the disadvantages of those pages are the reason for the increased request for safeguard which prevents the user from accessing, our study explains the possibility of identifying suspicious links from the URL-based features of its addresses, we demonstrate that our problem is consistent with machine learning algorithms, it also fits to the modern features of the continuously evolving distribution of malicious URLs, we have also developed the model for those predictive addresses and categorized it into safe or unsafe URL by using naive Bayes algorithm we also compare this work with the researchers' other studies.