Controlling spam Emails at the routers

Like it or not, unsolicited bulk commercial Email (aka "spam") has become a regular menu item on the Internet information diet. Every day, millions of people find their Email in-boxes clogged with vast quantities of spam. Moreover, the daily replenishment of all those in-boxes with new spam also consumes significant amount of network bandwidth. Dealing with spam is like fighting a battle against a large army; the most effective approach is to employ multiple tactics. However, almost all spam control methods that have been proposed and implemented follow the same basic theme of establishing a "front line" of defense at the end-user level. Thus, in this paper we propose a method for blocking the supply lines. More specifically, we identify spam at the router level and control it via rate limiting. Spam identification is done in two phases. In the first phase, we identify the bulk stream of Email messages and in second phase we apply Bayesian classifier to identify whether it is a spam. If a bulk Email stream is classified as a spam then we rate limit it (e.g. no more than one copy per minute). Our proposed method exploits the short timespan delivery and bulkiness of spam Emails. We use publicly available spam corpus to evaluate our proposed scheme and in the other set of experiments, we work on one month sanitized log of our department Emails to provide the representative results.