Journal
PATTERN RECOGNITION LETTERS
Volume 32, Issue 10, Pages 1436-1446Publisher
ELSEVIER
DOI: 10.1016/j.patrec.2011.03.022
Keywords
Spam filtering; Image spam; Document categorisation
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Funding
- Regione Autonoma della Sardegna [FSE 2007-2013, L.R.7/2007]
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In their arms race against developers of spam filters, spammers have recently introduced the image spam trick to make the analysis of emails' body text ineffective. It consists in embedding the spam message into an attached image, which is often randomly modified to evade signature-based detection, and obfuscated to prevent text recognition by OCR tools. Detecting image spam turns out to be an interesting instance of the problem of content-based filtering of multimedia data in adversarial environments, which is gaining increasing relevance in several applications and media. In this paper we give a comprehensive survey and categorisation of computer vision and pattern recognition techniques proposed so far against image spam, and make an experimental analysis and comparison of some of them on real, publicly available data sets. (C) 2011 Elsevier B.V. All rights reserved.
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