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Title

Detecting Phishing E-mails by Heterogeneous Classification

AuthorsCastillo Sobrino, María Dolores del ; Iglesias, Ángel ; Serrano Moreno, José Ignacio
Keywordse-mail classification
web filtering
multistrategy learning
Issue DateDec-2007
PublisherSpringer
CitationLecture Notes in Computer Science vol. 4881/2007, pp. 296-305
AbstractThis paper presents a system for classifying e-mails into two categories, legitimate and fraudulent. This classifier system is based on the serial application of three filters: a Bayesian filter that classifies the textual content of e-mails, a rule- based filter that classifies the non grammatical content of e-mails and, finally, a filter based on an emulator of fictitious accesses which classifies the responses from websites referenced by links contained in e-mails. This system is based on an approach that is hybrid, because it uses different classification methods, and also integrated, because it takes into account all kind of data and information contained in e-mails. This approach aims to provide an effective and efficient classification. The system first applies fast and reliable classification methods, and only when the resulting classification decision is imprecise does the system apply more complex analysis and classification methods.
Publisher version (URL)http://www.springerlink.com/content/j6888822hmjt5862/
URIhttp://hdl.handle.net/10261/21694
DOI10.1007/978-3-540-77226-2_31
Appears in Collections:(IAI) Artículos
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