TY  - JOUR
T1  - An Automatic Detection of e-Banking Phishing Web Pages with NEFCLASS Back Propagation
AU - Malathi, P. AU - Vivekanandan, P. 
JO  - Asian Journal of Information Technology
VL  - 13
IS  - 3
SP  - 156
EP  - 169
PY  - 2014
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2014.156.169
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2014.156.169
KW  - e-Banking
KW  -webpage
KW  -phishers
KW  -phishing attack
KW  -fuzzy logic
KW  -neural networks
AB  - 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.
ER  -