Decision Tree Classifier for Classification of Phishing Website with Info Gain Feature Selection

Abstract

Security of the information is very challenging task for every organizations and institute due to increasing demand of information and communication technology. Phishing attack is one of the important issues to access the sensitive information from unauthorized person. Data mining based classification intelligent techniques play very important role to classify the phishing and non phishing attack. In this research work, we have proposed decision tree technique and Info gain feature selection technique (FST) using different top selected feature subsets for developing computationally efficient model for classification of phishing websites. Our proposed Decision Tree (DT) technique gives better classification accuracy as 99.80% with 15 numbers of features in case of Info gain FST.

Authors and Affiliations

A. K Shrivas, Ramkishun Surayawanshi

Keywords

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  • EP ID EP24161
  • DOI -
  • Views 285
  • Downloads 9

How To Cite

A. K Shrivas, Ramkishun Surayawanshi (2017). Decision Tree Classifier for Classification of Phishing Website with Info Gain Feature Selection. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 5(5), -. https://europub.co.uk/articles/-A-24161