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TitleSpam email filtering using network-level properties
Author(s)Cortez, Paulo
Correia, André
Sousa, Pedro
Rocha, Miguel
Rio, Miguel
KeywordsAnti-Spam filtering
Text Mining
Naive Bayes
Support Vector Machines
Issue date2010
JournalLecture Notes in Computer Science
CitationCORTEZ, Paulo [et al.] - Spam email filtering using network-level properties. In PERNER, Petra, ed. lit. – “Advances in Data Mining : applications and theoretical aspects : proceedings of the Industrial Conference on Data Mining (ICDM 2010), 10, Berlin, Germany, 2010” [Em linha]. Berlin : Springer, 2010. (Lecture Notes in Artificial Intelligence ; 6171) [Consult. 25 Ag. 2010]. p. 476-489. Disponível em: ISBN 978-3-642-14399-1.
Abstract(s)Spam is serious problem that affects email users (e.g. phishing attacks, viruses and time spent reading unwanted messages). We propose a novel spam email filtering approach based on network-level attributes (e.g. the IP sender geographic coordinates) that are more persistent in time when compared to message content. This approach was tested using two classifiers, Naive Bayes (NB) and Support Vector Machines (SVM), and compared against bag-of-words models and eight blacklists. Several experiments were held with recent collected legitimate (ham) and non legitimate (spam) messages, in order to simulate distinct user profiles from two countries (USA and Portugal). Overall, the network-level based SVM model achieved the best discriminatory performance. Moreover, preliminary results suggests that such method is more robust to phishing attacks.
TypeConference paper
Publisher version© Springer. The original publication is available at:
AccessOpen access
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings
DI/CCTC - Artigos (papers)
DSI - Engenharia da Programação e dos Sistemas Informáticos

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