Combining visual and textual features for filtering spam emails

The presence of 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 this paper we present a system for overcoming some of the problems that still remain with spam filters when checking emails that can contain attached images. A comparison with other state-of-the-art spam filters on a database containing both image and textual spam is also reported.