A novel feature extraction approach in SMS spam filtering for mobile communication: one-dimensional ternary patterns

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dc.authorid0000-0001-5167-1101en_US
dc.authorid0000-0003-0710-0867en_US
dc.contributor.authorKaya, Yılmaz
dc.contributor.authorErtuğrul, Ömer Faruk
dc.date.accessioned2019-07-04T13:13:40Z
dc.date.available2019-07-04T13:13:40Z
dc.date.issued2016-10-19en_US
dc.departmentBatman Üniversitesi Mühendislik - Mimarlık Fakültesi Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.description.abstractThe importance and utilization of mobile communication are increasing day by day, and the short message service (SMS) is one of them. Although SMS is a widely used communication way, it brings together a major problem, which is SMS spam messages. SMS spams do not only use vain in the mobile communication traffic but also disturb users. Based on this fact, blacklisting methods, statistical methods which are built on the frequency of occurrence of words or characters, and machine learning methods have been employed. Because punishments and legal laws are not enough to solve this problem and the Group Special Mobile number of SMS spam can easily be changed, a content-based approach must be proposed. Content-based methods showed high success in spam e-mail filtering, but it is hard in the SMS spam filtering because SMS messages are extremely short and generally contains many abbreviations. In this study, an image processing method, local ternary pattern was improved to extract features from SMS messages in the feature extraction stage. In the proposed one-dimensional ternary patterns, firstly, text message was converted to their UTF-8 values. Later, each character (its UTF-8 value) in the message was compared with its neighbors. Two different feature sets were extracted from the results of these comparisons. Finally, some machine learning methods were employed to classify these features. In order to validate the proposed approach, three different SMS corpora were used. The achieved accuracies and other employee performance measures showed that the proposed approach, one-dimensional ternary patterns, can be effectively employed in SMS spam filtering.en_US
dc.identifier.citationKaya, Y., Ertuğrul, Ö F. (2016). A novel feature extraction approach in SMS spam filtering for mobile communication: One-dimensional ternary patterns. Security and Communication Networks, 9(17), pp. 4680-4690. https://doi.org/10.1002/sec.1660en_US
dc.identifier.endpage4690en_US
dc.identifier.issn1939-0114
dc.identifier.issn1939-0122
dc.identifier.issue17en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage4680en_US
dc.identifier.urihttps://doi.org/10.1002/sec.1660
dc.identifier.urihttps://hdl.handle.net/20.500.12402/2190
dc.identifier.volume9en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherWiley-Blackwellen_US
dc.relation.isversionof10.1002/sec.1660en_US
dc.relation.journalSecurity and Communication Networksen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsAttribution-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-sa/3.0/us/*
dc.subjectSMSen_US
dc.subjectSpam Filteringen_US
dc.subjectTernary Patternsen_US
dc.subjectText Miningen_US
dc.titleA novel feature extraction approach in SMS spam filtering for mobile communication: one-dimensional ternary patternsen_US
dc.typeArticleen_US

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