The author reflects on issues related to spamming. He discusses the methods used by spam writers to get through filtering programs. According to the author, many spams include a long addendum of random words or irrelevant text which aims to dilute the spamminess of the message so that the overall score might fall below the rejection threshold.

WHAT'S MOST remarkable about out the question posed in my title is that I probably don't need to explain it. If you have checked your e-mail anytime in the past few years, you know all about "V.i.a.g.r.a" and "V!A6RA" and "\/lagra," not to mention "C1aL|$" and "Rrol,x Rep,ica" and--let's not be bashful about this--"pen1s en1argement." As spam has been proliferating in everyone's inbox, it has also been mutating madly, presumably in an effort to evade the filters that most of us now have in place.

I wrote a column on spam four years ago, when the plague was still in its early stages. I reported then, in breathless amazement, that I was getting as many as 300 spares a month! Now, if the tally ever dropped that low, I would worry that something had gone wrong with my Internet connection. Spam has become one of modem life's little assaults on our patience and dignity, like traffic jams and cell-phone ringtones and getting wanded at the airport. We all hope it will just go away, but in the meantime we learn to live with it. One way of coping is to set your emotions aside and look upon the irritant as an object of dispassionate study.

At the deepest level, spam is a social and economic phenomenon rather than a technological one. The senders and the intended recipients are people, not computers. Nevertheless, there's the potential for some interesting computation in the making of the stuff, and even moreso in the defenses that help keep it in check. Cre@tive spelling is part of this story, and so is the automated production of meaningless drivel. On the defensive side, tools from statistics, pattern analysis and machine intelligence have been brought to bear. Twenty years ago, who could have guessed that the most widely deployed application of computational linguistics and computational learning theory would be fending off nuisance e-mail?

The spam we see today is shaped in many ways by our own efforts to combat it. The process is often likened to an arms race, with threats met by countermeasures, which then bring counter-countermeasures, and so on. I prefer an immunological metaphor, where the contest is between a host organism and pathogens or parasites, and where both sides have to adapt and evolve in order to survive. In the case of bacteria and viruses, the vast majority never make it, but nature is profligate and can afford such high attrition; likewise spammers find it worth their while to send a million e-mails for a handful of responses.