Image Spam Filtering by Content Obscuring Detection

We address the problem of filtering image spam, a rapidly spreading kind of spam in which the text message is embedded into attached images to defeat spam filtering techniques based on the analysis of e-mail’s body text. We propose an approach based on low-level image processing techniques to detect one of the main characterstics of most image spam, namely the use of content obscuring techniques to defeat OCR tools. A preliminary experimental evaluation of our approach is reported on a personal data set of spam images publicly available.