An Ensemble Model for Classification of Phishing e-mail

Abstract

Phishing attack is one of the critical issues that access sensitive information from e-mail users like banking password, credit card information and other details. Phishing e-mail not only wastage the storage space in mailbox, decrease the communication band width, but it also damage and misuse the sensitive information. This paper presents the classification of phishing e-mail or non phishing e-mail. In this paper, we have used various classification techniques like C4.5, Classification and Regression Technique (CART), Support Vector Machine (SVM), BayesNet and its ensemble technique for classification of phishing e-mail. The ensemble of CART and SVM gives better actuary results as 99.03% in case of 80-20% training-testing partitions.

Authors and Affiliations

Akhilesh Kumar Shrivas, Sashibhushan Singh Mahto

Keywords

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  • EP ID EP22739
  • DOI -
  • Views 264
  • Downloads 4

How To Cite

Akhilesh Kumar Shrivas, Sashibhushan Singh Mahto (2016). An Ensemble Model for Classification of Phishing e-mail. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 4(10), -. https://europub.co.uk/articles/-A-22739