Computer security threats, spams, can interrupt your busy days by forcing you to stop your work and spend time in opening and deleting mails. It can even unleash a nasty virus in your organizations network thus crippling your servers or desktops.
Here are some of the spam filtering methods and techniques that tend to peg the rate of spam at anywhere from 50 to 90 percent of all emails on the Internet. As it is not possible to prevent spammers from sending junk but setting an anti-spam application can vastly reduce the amount of spam your staffers have to deal with. So, here are some of the anti-spam filter applications that employs one or more methods for filtering and identifying spam and stop it from reaching a user’s inbox.
As you read the descriptions of the email spam-filtering methods below, consider factors such as the scope of your current spam problem and how much work users at your nonprofit are willing to do to stop unwanted email.
Here the list goes!
They stop spam by categorizing senders as spammers or trusted users, and blocking or allowing their messages accordingly.
This popular spam-filtering method that blocks unwanted email from a preset list of senders the administrator create. These blacklist are list of email addresses / IP addresses that have been previously used to send spam.
- Real-Time Blackhole List
In this most real-time blackhole lists are maintained by third parties. The filter is connected to the third-party system each time an email comes in. It eliminates the need to maintain the list manually as the blacklists is updated in real time.
A whitelist works exactly opposite to blacklist. It lets you specify which senders to allow mail from; and then these addresses are placed on a trusted-users list. It is thus a quite strict filter that only uses a whitelist would mean that anyone who was not approved would automatically be blocked.
In this system only receiving mail server initially rejects messages from unknown users and sends a failure message to the originating server. If the mail server attempts to resend the message a second time, greylist assumes the message is not spam and lets it proceed to the recipient’s inbox.
Content-based filters evaluate words or phrases found in each individual message to determine whether an email is spam or legitimate. Following are some of its types –
- Word-Based Filters
It simply blocks any email that contains certain terms.
- Heuristic Filters
Heuristic filter takes multiple terms found in an email by scanning the contents of incoming emails and assigning points to words or phrases.
- Bayesian Filters
In this email filtering system, the laws of mathematical probability are used to determine which messages are legitimate and which are spam.
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