This is a reference article describing the benefits of Bayesian filtering in GFI MailEssentials.
Bayesian filtering is widely acknowledged by leading experts and publications to be the best way to catch spam. A Bayesian filter uses a mathematical approach based on known spam and legitimate emails. This gives it a tremendous advantage over other spam solutions that just check for keywords or rely on downloading signatures of known spam. GFI’s Bayesian filter uses an advanced mathematical formula and a dataset which is ‘custom-created’ for your installation: The spam data is continuously updated by GFI and is automatically downloaded by GFI MailEssentials, whereas the ham data is automatically collected from your outbound mail. This means that the Bayesian filter is constantly learning new spam tricks, and spammers cannot circumvent the dataset used. This results in a 98+% spam detection rate, after the required two-week learning period. In short, Bayesian filtering has the following advantages:
- Looks at the whole spam message, not just keywords or known spam signatures.
- Learns from your outbound mail (ham) and therefore reduces false positives greatly.
- Adapts itself over time by learning about new spam and new valid mail.
- Dataset is unique to the company, making it impossible to bypass.
- Multilingual and international.
- Articles by Bayesian guru Paul Graham: A Plan for Spam and So far, so good.
- Sorting the ham from the spam.
- How to train, update, and use the Bayesian database.