Visual and OCR-Based Features for Detecting Image Spam

Francesco Gargiulo, Carlo Sansone

Abstract

The presence of unsolicited bulk emails, commonly known as spam, can seriously compromise normal user activities, forcing them to navigate through mailboxes to find the - relatively few - interesting emails. Even if a quite huge variety of spam filters has been developed until now, this problem is far to be resolved since spammers continuously modify their malicious techniques in order to bypass filters. In particular, in the last years spammers have begun vehiculating unsolicited commercial messages by means of images attached to emails whose textual part appears perfectly legitimate. In this paper we present a method for overcoming some of the problems that still remain with state-of-the-art spam filters when checking images attached to emails. Results on both personal and publicly available email databases are pre- sented, in order to assess the performance of the proposed approach.

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Paper Citation


in Harvard Style

Gargiulo F. and Sansone C. (2008). Visual and OCR-Based Features for Detecting Image Spam . In Proceedings of the 8th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2008) ISBN 978-989-8111-42-5, pages 154-163. DOI: 10.5220/0001740801540163


in Bibtex Style

@conference{pris08,
author={Francesco Gargiulo and Carlo Sansone},
title={Visual and OCR-Based Features for Detecting Image Spam},
booktitle={Proceedings of the 8th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2008)},
year={2008},
pages={154-163},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001740801540163},
isbn={978-989-8111-42-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2008)
TI - Visual and OCR-Based Features for Detecting Image Spam
SN - 978-989-8111-42-5
AU - Gargiulo F.
AU - Sansone C.
PY - 2008
SP - 154
EP - 163
DO - 10.5220/0001740801540163