Towards the integration of diverse spam filtering techniques
Calton Pu, S. Webb, Oleksii Kolesnikov, Wenke Lee, R. Lipton · 2006
learning filters) use tokens, which are found during message content analysis, to separate spam from legitimate messages. The effectiveness of these token-based filters is due to the presence of token signatures (i.e., tokens that are invariant for the many variants of spam messages). Unfortunately, it is relatively easy for spammers to hide or erase these signatures through simple techniques such as misspellings (to confuse keyword filters) and camouflage (i.e., combined spam and legitimate content used to confuse statistical filters). Our hypothesis is that spam contains additional signatures which are more difficult to hide. A concrete example of this type of signature is the presence of URLs in spam messages which are used to induce contact from their victims. We believe diverse spam filtering tools should be developed to incorporate these additional signatures. Thus, in this paper, we discuss a new type of URL-based filtering which can be integrated with existing spam filtering techniques to provide a more robust anti-spam solution. Our approach uses the syntactic constraints of URLs to find them in emails, and then, it uses semantic knowledge and tools (e.g., search engines) to refine and sharpen the spam identification process. Index Terms — Email spam, Internet Applications, Spam filtering. I.