An Approach to the Identification and Prediction of Phishing Websites Using Classification Algorithms Based on Web Pages Characteristics

Document Type : Research Paper

Authors

Abstract

Today, the most important risk and
challenge addressed in e-commerce and e-banking is the risk of online fraud and phishing attacks.
Phishing attacks have
been one of widely used tools for attackers to steal
passwords and electronic
codes of users in e-exchanges
in cyberspace. In this type of fraud, fraudulent or
phisher sends emails with various claims
to the victim and directs the victim to his fake
pages by several different techniques. Then, he attempts
to steal sensitive information of users such as passwords. Web pages, emails and
phishing addresses have features that can be used
to detect these attacks. In this paper, an approach will be presented to identify and predict
phishing web sites using classification algorithms
based on web page features which has less error rate than other techniques
to deal with phishing attacks,
especially the similar techniques based on data mining algorithms. In the proposed approach,
the usable features in the detection of
phishing pages are weighted based
on the effect to detect these
attacks and then a pattern will be elicited to identify these attacks by applying classification algorithms on the relevant datasets. our approach can detect journal phishing attacks and has low error rate than previous approaches.

Keywords

References

 
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Journal of Modeling in Engineering
Volume 14, Issue 47
December 2016
Pages 213-227

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History

  • Receive Date: 05 September 2014
  • Revise Date: 19 February 2015
  • Accept Date: 05 May 2015

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