Detecting Malicious URL using Neural Network

Abstract

The increasing usage of internet, the network is facing different dangerous attacks. Phishing attacks represent a threat for internet user because attackers are tending to design web pages very easily, attacks are done by inserting executables or SQL injections to steal user’s sensitive information. In this research, we demonstrated how digital signature can improve URL detection. Also, we showed an effective steps organization can do to enhance their security over user’s usage and data. Therefore, it’s very important to develop new approaches for URL detection. Our paper presents the Malicious URL cyber-attacks by introducing a method for Malicious detection of URLs using Neural Network to classify the URLs according to its type, either normal or malicious. The use of neural network to detect malicious attacks is used by using feed-forward network and apply CICANDMAL2017 to it.