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A Multi-tier Ensemble Construction of Classifiers for Phishing Email Detection and Filtering

  • Jemal Abawajy
  • Andrei Kelarev
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7672)

Abstract

This paper is devoted to multi-tier ensemble classifiers for the detection and filtering of phishing emails. We introduce a new construction of ensemble classifiers, based on the well known and productive multi-tier approach. Our experiments evaluate their performance for the detection and filtering of phishing emails. The multi-tier constructions are well known and have been used to design effective classifiers for email classification and other applications previously. We investigate new multi-tier ensemble classifiers, where diverse ensemble methods are combined in a unified system by incorporating different ensembles at a lower tier as an integral part of another ensemble at the top tier. Our novel contribution is to investigate the possibility and effectiveness of combining diverse ensemble methods into one large multi-tier ensemble for the example of detection and filtering of phishing emails. Our study handled a few essential ensemble methods and more recent approaches incorporated into a combined multi-tier ensemble classifier. The results show that new large multi-tier ensemble classifiers achieved better performance compared with the outcomes of the base classifiers and ensemble classifiers incorporated in the multi-tier system. This demonstrates that the new method of combining diverse ensembles into one unified multi-tier ensemble can be applied to increase the performance of classifiers if diverse ensembles are incorporated in the system.

Keywords

Support Vector Machine Ensemble Method Ensemble Classifier Lower Tier Reasoning Community 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jemal Abawajy
    • 1
  • Andrei Kelarev
    • 1
    • 2
  1. 1.School of Information TechnologyDeakin UniversityBurwoodAustralia
  2. 2.School of SITEUniversity of BallaratBallaratAustralia

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