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User Guide - Kaspersky Lab

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SPAM Protection 171<br />

Allow all – lowest sensitivity level. Only email that contains phrases from the<br />

phrase black list, or senders listed on the address black list, are marked as<br />

spam. At this level, email is only processed using the black list, and all other<br />

features all disabled.<br />

By default, Anti-Spam is set to the Recommended sensitivity level. You can<br />

boost or reduce the level or edit the settings for the current level.<br />

To modify the level of sensitivity:<br />

In the Sensitivity section, move the slider up or down to the required<br />

setting. By adjusting the sensitivity level, you define the correlation<br />

between spam, potential spam, and accepted email factors (see 13.3.3<br />

on pg. 177).<br />

To modify the settings for the current sensitivity level:<br />

1. Open the application settings window and select Anti-Spam under<br />

Protection.<br />

2. Click on Customize under Sensitivity (cf. Figure 59).<br />

3. Edit spam protection parameters in the resulting window and click OK.<br />

As a result, the sensitivity level will be user customized.<br />

13.2. Training Anti-Spam<br />

Anti-Spam comes with a pre-installed email database containing fifty spam<br />

samples. You are advised to give the Anti-Spam module further training on your<br />

own emails.<br />

There are several approaches to training Anti-Spam:<br />

• Use the Training Wizard (see 13.2.1 on pg. 172)<br />

• Train Anti-Spam with outgoing emails (see 13.2.2 on pg. 172)<br />

• Train directly while working with email (see 13.2.3 on pg. 173), using<br />

special buttons in the email client tools panel or menu items<br />

• Training in Anti-Spam reports (see 13.2.4 on pg. 174)<br />

The best method is to use the Training Wizard from the very onset of using Anti-<br />

Spam, as it can train Anti-Spam on a large number of emails.<br />

Note that you cannot train Anti-Spam with more than 50 emails per folder. If<br />

there are more emails in the folder, the program will use fifty for training.

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