• DocumentCode
    180
  • Title

    A Survey of Phishing Email Filtering Techniques

  • Author

    Almomani, Ammar ; Gupta, B.B. ; Atawneh, Samer ; Meulenberg, A. ; Almomani, Eman

  • Author_Institution
    Nat. Adv. IPv6 Centre (NAV6), Univ. Sains Malaysia (USM), Nibong Tebal, Malaysia
  • Volume
    15
  • Issue
    4
  • fYear
    2013
  • fDate
    Fourth Quarter 2013
  • Firstpage
    2070
  • Lastpage
    2090
  • Abstract
    Phishing email is one of the major problems of today´s Internet, resulting in financial losses for organizations and annoying individual users. Numerous approaches have been developed to filter phishing emails, yet the problem still lacks a complete solution. In this paper, we present a survey of the state of the art research on such attacks. This is the first comprehensive survey to discuss methods of protection against phishing email attacks in detail. We present an overview of the various techniques presently used to detect phishing email, at the different stages of attack, mostly focusing on machine-learning techniques. A comparative study and evaluation of these filtering methods is carried out. This provides an understanding of the problem, its current solution space, and the future research directions anticipated.
  • Keywords
    Internet; computer crime; learning (artificial intelligence); unsolicited e-mail; Internet; financial losses; machine-learning techniques; phishing email attacks; phishing email filtering techniques; Authentication; Classification; Electronic mail; Machine learning; Phishing; Authentication; Classifiers; Filtering; Machine learning; Network level protection; Phishing email;
  • fLanguage
    English
  • Journal_Title
    Communications Surveys & Tutorials, IEEE
  • Publisher
    ieee
  • ISSN
    1553-877X
  • Type

    jour

  • DOI
    10.1109/SURV.2013.030713.00020
  • Filename
    6489877