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An Analysis of the Effectiveness of Personalized Spam Using Online Social Network Public Information

  • Enaitz EzpeletaEmail author
  • Urko Zurutuza
  • José María Gómez Hidalgo
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 369)

Abstract

Unsolicited email campaigns remain as one of the biggest threats affecting millions of users per day. 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. 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 analyzed response of personalized spam sent to users according to their profile. Finally we demonstrate the effectiveness of these profile-based templates to circumvent spam detection.

Keywords

Spam Security Facebook Personalized spam Online social networks 

Notes

Acknowledgments

This work has been partially funded by the Basque Department of Education, Language policy and Culture under the project SocialSPAM (PI_2014_1_102).

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Enaitz Ezpeleta
    • 1
    Email author
  • Urko Zurutuza
    • 1
  • José María Gómez Hidalgo
    • 2
  1. 1.Electronics and Computing DepartmentMondragon UniversityArrasate-MondragónSpain
  2. 2.Pragsis Technologies Manuel TovarMadridSpain

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