Detection of Illegitimate Emails Using Boosting Algorithm

  • Sarwat Nizamani
  • Nasrullah Memon
  • Uffe Kock Wiil
Part of the Lecture Notes in Social Networks book series (LNSN)


In this paper, we report on experiments to detect illegitimate emails using boosting algorithm. We call an email illegitimate if it is not useful for the receiver or for the society. We have divided the problem into two major areas of illegitimate email detection: suspicious email detection and spam email detection. For our desired task, we have applied a boosting technique. With the use of boosting we can achieve high accuracy of traditional classification algorithms. When using boosting one has to choose a suitable weak learner as well as the number of boosting iterations. In this paper, we propose suitable weak learners and parameter settings for the boosting algorithm for the desired task. We have initially analyzed the problem using base learners. Then we have applied boosting algorithm with suitable weak learners and parameter settings such as the number of boosting iterations. We propose a Naive Bayes classifier as a suitable weak learner for the boosting algorithm. It achieves maximum performance with very few boosting iterations.


Support Vector Machine Base Learner Training Instance Weak Learner Decision Tree Algorithm 
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/Wien 2011

Authors and Affiliations

  • Sarwat Nizamani
    • 1
    • 2
  • Nasrullah Memon
    • 1
    • 3
  • Uffe Kock Wiil
    • 1
  1. 1.Counterterrorism Research Lab, The Maersk Mc-Kinney Moller InstituteUniversity of Southern DenmarkOdenseDenmark
  2. 2.University of SindhJamshoroPakistan
  3. 3.Hellenic American UniversityManchesterUSA

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