Machine Learning Based Malicious URL Detection (original) (raw)

Today Internet technology has become an essential part of our life for education, entertainment, gaming, banking and communication. In this modern digital era, it is very easy to have any information by one click. But everything which has pros and cons, as we have any information at our tips but Internet is an attack platform also. When we use Internet to make our work easy same time many attacker try to steal information from our system. There are many means for attacking, malicious URL one of them. When a user visits a website, which is malicious then it triggers a malicious activity which is predesigned. Hence, there are various approaches to find dangerous URL on the Internet. In this paper, we are using machine learning approach to detect malicious URLs. We used ISCXURL2016 dataset and used J48, Random forest, Lazy algorithm and Bayes net classifiers. As performance metrics, we calculate accuracy, TPR, FPR, precision and recall.