On Extendable Software Architecture for Spam Email Filtering
Wanli Ma, Dat Thanh Tran, Dharmendra Kumar Sharma · University of Canberra Research Portal · 2007
The research community and the IT industry have invested significant effort in fighting spam emails. There are many different approaches, ranging from white listing, black listing, reputation ranking, postage, legislation, and content scanning etc. Until every ISP obeys the same rules, content scanning based spam email filters still have a significant role to play in fighting spam emails. There are many content scanning based spam email filters available and also in operation. Yet we are still inundated with spam emails everyday. This is not because the filters are not powerful enough, but because the filtering systems are not flexible enough to adapt the new development of spam techniques, such as HTML tagging, image based spam, and keyword obfuscating etc. In this paper, we propose to use dynamic multiple normalizers as the preprocessors for spam filters. The normalizers convert an email to its plain text format, called normalization. With the help of the normalizers, spam filters only need to deal with plain text format, which is what the filters are good at. The flexibility of the proposed architecture does not only make the adoption to the new creations of spammers easier but also makes the integration to the other spam fighting technologies easier.