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Webpages Classification with Phishing Content Using Naive Bayes Algorithm

  • Jorge Enrique Rodríguez RodríguezEmail author
  • Víctor Hugo Medina GarcíaEmail author
  • Nelson Pérez CastilloEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1027)

Abstract

Phishing attacks cause people to be scammed and cheated because of the impossibility to visually detect fraudulent websites. As is known, the attack occurs from emails sent to collect or update information supposedly from an entity, there are also cases of phone calls or instant messages. There is ignorance of such attacks by people in general, which means that the user is not alerted, which means that he is not attentive to the digital certificates present on the page that authenticate the content of the same. For this reason, the web pages designed have required tools that counteract and alert the user of the “phished” webpages, which commit the theft of money from the account from which information has been provided.

Keywords

Webpage Suspicious Legitimate Phishing Naive Bayes Machine learning Data mining 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.District University “Francisco José de Caldas”BogotáColombia

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