An Ensemble Model for Identification of Phishing Website

Jaspreet Kaur Virdi
2017 International Journal for Research in Applied Science and Engineering Technology  
Identification of phishing websites is very challenging task for every internet and e-mail users. To protect the information from unauthorized person classification of phishing websites is very important. In this research work , we have used many data mining based classification techniques like C4.5, SimpleCart, Random tree, SVM and MLP for classification of phishing websites with different data partitions like 75% training and 25% testing" 80% training and 20% testing and 85% training and 15%
more » ... esting. To develop a robust model , we have ensemble the models with different combinations. We have achieved better accuracy with ensemble of C4.5, SimpleCart , MLP and Random tree with all data partitions, but it achieved best accuracy as 97.16% in case of 85-15% data partition.
doi:10.22214/ijraset.2017.4205 fatcat:2wmoczrdsrdntlyhcaolqyf5yi