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A study of the personalization of spam content using Facebook public information.pdf (260.7Kb)
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Title
A study of the personalization of spam content using Facebook public information
Author
Ezpeleta Gallastegi, Enaitz
Zurutuza Ortega, Urko
Author (from another institution)
Gómez Hidalgo, José María
Research Group
Análisis de datos y ciberseguridad
Published Date
2017
Publisher
Oxford University Press
Keywords
spam
security
Facebook
personalized spam
online social networks
Abstract
Millions 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 r ... [+]
Millions 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. [-]
URI
http://hdl.handle.net/20.500.11984/1179
Publisher’s version
http://dx.doi.org/10.1093/jigpal/jzw040
ISSN
1367-0751 Print
Published at
Logic Journal of the IGPL  Vol. 25. Nº. Pp. 30–41. 1 February, 2017
Document type
Article
Version
Postprint – Accepted Manuscript
Rights
© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
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Open Access
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  • Articles - Engineering [183]
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