Nahid Doustmohammadi - Faculty of Engineering, Urmia University, Urmia, West Azerbaijan Province, Iran
Reza Babazadeh - Faculty of Engineering, Urmia University, Urmia, West Azerbaijan Province, Iran

Today, spam-identification has become a very important issue for individuals. Controlling all messages is costly, in addition to being time-consuming. In this article, a brief introduction to current spam-identification methods is given, and then a new method of spam-identification using neural networks is presented. Unlike many methods that use the Subject of the messages for spam-identification, this method considers the body of the email message. Furthermore, all words in the message are used. This attribute increases the accuracy of this method compared to other methods. This method is 94% accurate.

Spam, email, neural networks, content-focused methods