2024-03-29T15:51:16Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/216942016-02-16T06:22:03Zcom_10261_96com_10261_4col_10261_349
Castillo Sobrino, María Dolores del
Iglesias, Ángel
Serrano Moreno, José Ignacio
2010-02-26T11:15:10Z
2010-02-26T11:15:10Z
2007-12
Lecture Notes in Computer Science vol. 4881/2007, pp. 296-305
http://hdl.handle.net/10261/21694
10.1007/978-3-540-77226-2_31
This 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.
eng
openAccess
e-mail classification
web filtering
multistrategy learning
Detecting Phishing E-mails by Heterogeneous Classification
capítulo de libro