Modeling Spammer Behavior: Artificial Neural Network vs. Naïve Bayesian Classifier
MetadataShow full item record
The exponential growth of spam emails in recent years is a fact of life. Internet subscribers world-wide are unwittingly paying an estimated €10 billion a year in connection costs just to receive “junk” emails, according to a study undertaken for the European Commission. Though there is no universal definition of spam, unwanted and unsolicited commercial email as a mass mailing to a large number of recipients is basically known as the junk email or spam to the internet community. Spams are considered to be potential threat to Internet Security. Spam's direct effects include the consumption of computer and network resources and the cost in human time and attention of dismissing unwanted messages. More importantly, these ever increasing spams are taking various forms and finding home not only in mailboxes but also in newsgroups, discussion forums etc without the consent of the recipients. Overflowing mailboxes are overwhelming users, causing newsgroups and discussion forums to be flooded with irrelevant or inappropriate messages. As a consequence, users are getting discouraged not to use them anymore though these systems can provide numerous benefits to them.
Artificial Neural Networks - Application
© 2011 The Author(s). This is an open-access file distributed under the terms of the under CC BY-NC-SA 3.0 license, which permits non-commercial, unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Information and Computing Sciences not elsewhere classified