Top Vendors for Internet Blocking and Filtering

Any business with computers connected to the Internet needs Internet blocking or filtering services. If you don't want your employees online at all, blocking software is necessary. If you want to limit what your employees can see online, a filter is what you need. And because spam wastes your employees' time and opens up your business computers to time-consuming and costly viruses and worms, all businesses sending and receiving e-mails need spam filters.
As you shop for the best blocking or filtering services for your business, you may run across some terms you're not familiar with. However, these terms are important to understand if you're going to spend money on a system that truly works for you. With that in mind, here are some common terms used to describe how filters work.

Backlist

Many filtering and blocking programs create a backlist, or a list of suspected spam e-mail addresses or websites deemed inappropriate. Backlist e-mails never enter your inbox and backlist websites cannot be accessed.

Client-based filter

A client-based filter is a piece of software that's installed on an individual computer and allows users to block certain types of material on the Internet. Client-based filters run on the computer simultaneously with the Internet browser.

Server-based filter

A server-based filter does not allow the computer user direct control over the filtering process. Any information that comes into the computer has already been filtered. Filtering software is installed on a host server (like a web server).

False positive

A false positive is when filtering software sets aside an e-mail as spam when it actually is not spam.

False negative

A false negative is when filtering software does not set aside an e-mail as spam when it is actually spam.

Bayesian based filter

Bayesian based filters (sometimes just called Bayesian filters) are named after Thomas Bayes, an 18th century man who created a formula that allows us to know the probability of an occurring event. A Bayesian based filter must be taught to distinguish between desirable and undesirable e-mails.