Abstract: Phishing webpage that mimic the webpage of legitimate, to steal information from users which become the fashionable practice and sophistical growing among the perpetrators of the Web. This phishing scams become a gigantic problem from e-Bankers and e-Commerce users. It is dynamic and very complex problem to classify phishing webpage because of alike absolute character of legitimate webpage. This study presents an approach to overcome the complicatedness for foretelling or classifying e-Banking phishing webpage. The classification of phishing webpage leads to the subjective consideration of various factors, the Neuro-Fuzzy Classification (NEFCLASS) Back Propagation algorithm can be an effectual analysis of classification model. The NEFCLASS Back Propagation algorithm analyzes the webpage in natural way in human intellectual manner. The various multi modal features are considered in this study for effectual classification with three phishing stratums. Thirty features are extracted are grouped in six different property that under three stratums, respectively.
P. Malathi and P. Vivekanandan, 2014. An Automatic Detection of e-Banking Phishing Web Pages with NEFCLASS Back Propagation. Asian Journal of Information Technology, 13: 156-169.