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New Ways Spammers are Getting Past those Filters Spam is one of the most annoying by-products of email and has become and even more epic business problem. Clever self-learning methods and neural networks are the latest ways to combat spam, but many do not work well for corporate use, and the normal email user is always finding that the spammers are getting past their filters. Spammers these days are smart and have come up with tricky ways to confuse these filters into thinking that they are sending legitimate email, when really they are distributing spam. Keeping on top of this growing problem has been difficult because of the problems filters are having correctly identifying an email as spam.
Unsolicited emails are growing at an alarming rate of 5% a month according to a Kessler International survey, and that means thousands of
unwanted emails per week. These messages often total 75% of the messages an enterprise email gateway must process which clogs downstream wires and servers.
Spam also sucks up employee time, and much of the messages are so obscene and inappropriate for a business environment that it is causing a huge headache for workers. Nucleus Research reports that nuisance email costs $874 per person annually in lost productivity. This is an astounding figure and one that warrants better spam protection.
One solution that has been discussed considerably is government intervention, but network professionals arent holding out for that kind of relief any time soon. This means exterminating spam has become the task of the network team. This is a difficult task to undergo because email marketers constantly find ways to work around existing email filters. The anti-spam software venders keep creating new filters intended to spot these spammers latest tricks, but are having a hard time keeping up. Network executives must frequently update software to get the most effective filters, however the more filtering they switch on, the greater chance that legitimate email will get mislabeled and deleted as spam.
The newest batch of filters promises to stop this back and forth cycle. They are based on self-learning or machine-learning technologies that attempt to adapt automatically to spammers new tricks, while protecting the legitimate email. Bayesian filtering is a type of filter that has been implemented in a growing number of anti-spam products, which range from open source product SpamAssassin to an enterprise-class spam-detection module from the start up company, ProofPoint. This is the most talked about technology, with neural networks also generating a buzz.
Unlike the older anti-spam technologies, such as dictionary scans, blacklisting, and heuristic, these filters are not always an easy solution for corporations. Bayesian filtering is one of several tests that determine the e-mail's overall spam probability. Once that's done, the anti-spam tool embeds a spam rating in the message header and then typically sends the e-mail on to the client's e-mail software. It then uses the tag to sort or delete the message, according to user instructions.
Should the filter make an error and call a legitimate e-mail spam or questionable, or tagging spam as legitimate, the end user would send the falsely labeled message to the correct folder. The filter uses these folders to reteach itself daily or per user-specified frequency. Regular training assures that the filter automatically learns the latest spammer tricks. These include things like using garbage characters in the subject line and spaces between letters.
As long as spam remains a cat-and-mouse game between companies and e-mail marketers, vendors will be pressured to make constant upgrades to include smarter and more adaptive filters. At a 5% increase per month, it is time to investigate automated filtering techniques and stop letting spam rule your inbox. Your companys productivity will thank you and it will cause everyone a lot fewer headaches in the future.
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