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Acronis Internet Security Suite 2010 Manual

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Image Filter
Since avoiding heuristic filter detection has become quite a challenge, nowadays'
inbox folders are full with more and more messages only containing an image with
unsolicited content. To cope with this growing problem, the Image filter compares
the image signature from the e-mail with those from the Acronis Internet Security
Suite 2010 database. In case of a match the e-mail will be tagged as SPAM.
URL Filter
Almost all spam messages include links to various web locations. These locations
usually contain more advertising and the possibility to buy things, and, sometimes,
they are used for phishing.
Acronis maintains a database of such links. The URL filter checks every URL link in
a message against its database. If a match is made, the message is tagged as SPAM.
NeuNet (Heuristic) Filter
The NeuNet (Heuristic) filter performs a set of tests on all the message
components, (i.e. not only the header but also the message body in either HTML or
text format), looking for words, phrases, links or other characteristics of SPAM. Based
on the results of the analysis, it adds a SPAM score to the message.
The filter also detects messages marked as SEXUALLY-EXPLICIT: in the subject
line and tags them as SPAM.
Note
Starting May 19, 2004, spam that contains sexually oriented material must include
the warning SEXUALLY-EXPLICIT: in the subject line or face fines for violations
of federal law.
Bayesian Filter
The Bayesian filter module classifies messages according to statistical information
regarding the rate at which specific words appear in messages classified SPAM as
compared to those declared NON-SPAM (by you or by the heuristic filter).
This means, for example, if a certain four-letter word is seen to appear more often
in SPAM, it is natural to assume there is an increased probability that the next
incoming message that includes it actually IS SPAM. All relevant words within a
message are taken into account. By synthesizing the statistical information, the
overall probability for the whole message to be SPAM is computed.
This module presents another interesting characteristic: it is trainable. It adapts
quickly to the type of messages received by a certain user, and stores information
about all. To function effectively, the filter must be trained, meaning, to be presented
with samples of SPAM and legitimate messages, much like a hound is primed to
Antispam
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