Security from Phishing Attack on Internet using Evolving Fuzzy Neural Network

Abstract

In recent years with the increase of cyber-attacks, data defense plays an essential part. The protecting of data has been the toughest obstacles now a days. Different countries and businesses take a wide range of steps to combat such cyber-attacks. The rise of online technologies has resulted in unceasingly creative challenges to surveillance critical infrastructure. A few of these severe risks would be the use of phishing to deprive clients of web servers by using counterfeit email or URLs. Hence it is essential for employers to focus on application server sensitivity in the mitigation of phishing attacks. The intellectual ransom ware safety of internet study was based on mathematical methods, using fuse algorithms and a variety of resources that collect functions. The knowledgeable method to phishing protection was strengthened. The results demonstrate that phishing websites can be more reliably identified by the parameter estimation from consolidated databases. This would be a very difficult challenge to identify and delete the phishing pages, as the approaches usually involve different strategies and methodologies. This article explores how easily we use the neural network to deal with fake websites and to apply it by means of fuzzy logic techniques.

Index Terms: Fuzzy Neural Networks, Phishing Attack, Cyber Security, Internet