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dc.contributor.authorEzpeleta Gallastegi, Enaitz
dc.contributor.authorZurutuza Ortega, Urko
dc.contributor.otherGómez Hidalgo, José María
dc.date.accessioned2019-04-04T11:40:13Z
dc.date.available2019-04-04T11:40:13Z
dc.date.issued2017
dc.identifier.issn1367-0751 Printen
dc.identifier.issn1368-9894 Onlineen
dc.identifier.otherhttps://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=124602en
dc.identifier.urihttp://hdl.handle.net/20.500.11984/1179
dc.description.abstractMillions of users per day are affected by unsolicited email campaigns. Spam filters are capable of detecting and avoiding an increasing number of messages, but researchers have quantified a response rate of a 0.006% [1], still significant to turn a considerable profit sending millions of emails, as the spammers do. While research directions are addressing topics such as better spam filters, or spam detection inside online social networks, in this paper we demonstrate that a classic spam model using online social network information can harvest a 7.62% of click-through rate. We collect email addresses from the Internet, complete email owner information using their public social network profile data, and analyze response of personalized spam sent to users according to their profile using a fake website. Finally we demonstrate the effectiveness of these profile-based emails to circumvent spam detection and we compare results between typical spam and personalized spam.en
dc.description.sponsorshipGobierno Vascoes
dc.language.isoengen
dc.publisherOxford University Pressen
dc.rights© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.comen
dc.subjectspamen
dc.subjectsecurityen
dc.subjectFacebooken
dc.subjectpersonalized spamen
dc.subjectonline social networksen
dc.titleA study of the personalization of spam content using Facebook public informationen
dc.typeinfo:eu-repo/semantics/articleen
dcterms.accessRightsinfo:eu-repo/semantics/openAccessen
dcterms.sourceLogic Journal of the IGPLen
dc.description.versioninfo:eu-repo/semantics/acceptedVersionen
local.contributor.groupAnálisis de datos y ciberseguridades
local.description.peerreviewedtrueen
local.identifier.doihttp://dx.doi.org/10.1093/jigpal/jzw040en
local.relation.projectIDGV/Proyectos de Investigación Básica y Aplicada 2014-2016/PC2014-08/CAPV/Seguimiento y filtrado de spam personalizado en medios sociales mediante modelos de difusión y análisis del contenido/SOCIALSPAMen
local.source.detailsVol. 25. Nº. Pp. 30–41. 1 February, 2017eu_ES


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