Spamming is overcrowding the Internet with copies of the same message. It reaches the Internet user even if he/she does not choose to receive the message. It is usually used for promoting brands and goods as it is seen as an easier and cost-effective way.
Recently, it has come to light that it is apparently a multibillion dollar industry wherein various companies indulge in it through professional spammers to promote their brands.
Virus Spam: In this method, a computer is infected with a particular type of virus that picks up email addresses from the address book and spams them.
Even though there are anti-spam laws, the spamming continues. However, there are various ways available to curb it, viz., filtering, blacklisting, whitelisting, and using spamfree channels. The filters to screen spam were initially located on the central servers. However, with increase in its volume and variety, they are now installed on the local computers.
Although, they are also installed on the central servers, they filter emails on the basis of its content. These filters consist of classifiers which can be either signature based or rule based.
Content or Rule-based Filters
These filters follow certain rules to separate the spam. There are certain assumptions made while designing these filters which are as follows:
- The user always assumes that the unsolicited emails are spam.
- The email or content that is posted several times is also considered as spam.
- All the users receive the same content.
Nevertheless, people do not classify all the unsolicited emails as spam, which is a drawback of this technology. Also, not necessarily all the mails that are posted several times are spam. It is also possible for more than a person to receive the same mail. For all these reasons, many filter makers have shifted to the Bayesian filtering.
Bayesian Filters (Learning filters)
The filters at the local machines do not screen mails based on their content, but according to the rules set by the software. These are called collaborative filters. When a user marks a mail as spam, a signature is created by the software and it is added to the database. The next time it encounters the signature in some other mail, it is marked as spam.
It makes a list of spammers and also the list of emails which are solicited. Some filtering techniques are based on blacklist, some on whitelist, and others on both. The blacklist filtering technique uses the signature based filtering technique. The whitelist filters, on the other hand, make a list on their own based on the activities of the user.