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While this may seem like a good idea from outset, a whitelist methodology is too restrictive for most people and, as virtually all spam e-mails carry a forged “from” address, there is little point in collecting this address to ban it in future as it is very unlikely to be same next time. There are bodies on internet that maintain a list of known “bad” sources of e-mail. Many filters today have ability to query these servers to see if message they are looking at comes from a source identified by this Internet-based blacklist, or RBL. While being quite effective, they do tend to suffer from “false positives” where good messages are incorrectly identified as spam. This happens often with newsletters.
Challenge/Response Filters “Open sesame!”
Challenge/Response filters are characterised by their ability to automatically send a response to a previously unknown sender asking them to take some further action before their message will be delivered. This is often referred to as a "Turing Test" - named after a test devised by British mathematician Alan Turing to determine if machines could “think”.
Recent years have seen appearance of some internet services which automatically perform this Challenge/Response function for user and require sender of an e-mail to visit their web site to facilitate receipt of their message.
Critics of this system claim it to be too drastic a measure and that it sends a message that "my time is more important than yours" to people trying to communicate with you.
For some low traffic e-mail users though, this system alone may be a perfectly acceptable method of completely eliminating spam from their inbox - one step above "Whitelist" system outlined above.
Community Filters “A united front”
These types of filters work on principal of "communal knowledge" of spam. When a user receives a spam message, they simply mark it as such in their filter. This information is sent to a central server where a “fingerprint” of message is stored. After enough people have “voted” this message to be spam, then it is stopped from reaching all other people in community.
This type of filtering can prove to be quite effective, although it stands to reason that it can never be 100% effective as a few people have to receive spam for it to be “flagged” in first place. Just like its similar cousin Internet black list (RBL), this system also can suffer from “false positives”, or messages incorrectly identified as spam.
Hopefully you are now armed with a little more information to be able to make an informed decision on best spam filter for you. For further information, consider reading reviews and articles found at http://www.whichspamfilter.com
Alan Hearnshaw is owner of http://www.whichspamfilter.com, a web site which conducts weekly in-depth reviews of current spam filters, provides help and guidance in fight against spam and provides a useful community forum. firstname.lastname@example.org
Alan Hearnshaw is a computer programmer and the owner of http://www.WhichSpamFilter.com, a site which provides weekly in-depth spam filter reviews, user help and guidance and a community forum.