Cyber fraud detection using evolving spiking neural network

With the rapid growth of the internet, most of the businesses are now moving online. Since the internet is ubiquitous and can be accessed from anywhere websites are susceptible to attacks. One of such attack is phishing website attack. In which an attacker creates a duplicate copy of the website and tries to pose it as a legitimate to steal user's information. So it is the utmost need to detect such phishing websites. Machine learning techniques have been successfully applied to detect the phishing websites. The neural network is one of the efficient ways for detecting these phishing attacks. In our work, we have applied the spiking neural network approach to detect these phishing websites. The spiking neural network is biologically inspired by neuroscience literature, evolving spiking neural classifier for the pattern classification problem. We have compared it with various other machine learning techniques and we show that the evolving spiking neural network performs better than the existing machine learning techniques.