What is the ESET Smart Security Antispam Module?

Antispam behaviour and user interaction

The Antispam module detects unsolicited email in two ways. The first is through a basic set of rules which are designed to automatically filter unwan These rules are by default included in the installation of the program. It is updated along with the virus signature database updates. Second, it is by means of the Bayesian filter. The Bayesian filter can be trained on a per-user basis. The user manually marks a sufficient number of incoming emails as legitimate messages or as spam.


If you regularly receive spam from a certain address, you can add it to Black List. If you wish to designate that messages from a certain address will never be marked as spam, add the address to White List. By default, the sender address in outgoing messages are automaticaly added to the Whitelist.


The following section is intended to explain how to proceed when an unsolicited message arrives


An unsolicited message has come to my inbox, what should I do?

If the message has not been filtered by the program, it is most likely an unknown type of unsolicited email and should be marked as spam. To do this, click Spam located on the Eset Smart Security Toolbar.


A message was marked as spam, but it's not spam

If a legitimate email was classified as spam, the message must be reclassified. Select Not Spam on the Eset Smart Security Toolbar.


I receive spam from a certain address on a regular basis

In the event that you consistently receive spam from a certain address, you can add the address to the Black List. To add an address to the Black List, click Add to BL on the Eset Smart Security Toolbar. The list of addresses added to Black List can be viewed in the main antispam protection setup window. To add/edit/delete an entry, right-click in the window.


Antispam marks messages from an address which is trusted

You can add addresses you consider trusted to the list of trusted addresses (White List). All addresses marked as trusted will be handled as not spam. To add an address to the list of trusted addresses, click Add to WL on the Eset Smart Security Toolbar.

Bayesian filter

Bayesian spam filtering is a very effective form of e-mail filtering used by almost all antispam products. It is able to identify unsolicited e-mail with a high degree of accuracy. The Bayesian filter can be trained on a per-user basis.


The functionality is based on the following principle: In the first phase, the process of learning takes place. The user manually marks a sufficient number of messages as legitimate messages or as spam (normally 200/200). The filter analyzes both categories and learns, for example, that spam usually contains words “rolex” or “viagra”, and legitimate messages are sent by family members or from addresses in the user’s contact list. Provided that a greater number of messages was processed, the Bayesian filter is able to assign to each message a certain “spam index” and thus decide on whether it is spam or not.

The main advantage is its flexibility. For example, if a user is a biologist, all incoming e-mails concerning biology or a relative fields of study will generally receive a lower probability index. If a message includes words that would otherwise qualify it as being unsolicited, but it is sent by someone from a contact list, it will be marked as legitimate, because senders from a contact list decrease overall spam probability.

The server-side control

The server-side control is a technique for identifying mass spam e-mail based on the number of received messages and the reactions of users. Each message leaves a unique digital "footprint" on the server based on the content of the message. Actually it is a unique ID number which tells nothing about the content of the e-mail. Two identical messages will have identical footprints, while different messages will have different footprints.

If a message is marked as spam, its footprint is sent to the server. If the server receives more identical footprints (corresponding to a certain spam message), the footprint is stored at the spam footprints database. When scanning incoming messages, the program sends the footprints of the messages to the server. The server returns information on which footprints correspond to messages already marked by users as spam.

Related NOD32 FAQ Category:
Home Edition/ESET Smart Security

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Does ESET Smart Security scan SSL (Secure Sockets Layer) traffic?
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