Artificial neural network filtering spam messages

Abstract

Spam messaging leads to the wastage of time and resources and is non-beneficial to the society. Spam message filtering techniques for preventing the harmful influence of spam messages have been studied. Among these studies, the methods that evaluate specific words or number of senders are generally used for spam filtering. However, these methods are inefficient when spam messages are in the form of short text messages. In this paper, we propose a spam message filtering method that is based on artificial neural networks. The input neurons of the neural network are the number of special characters, the URL, and specific nouns. Experiments with the developed neural network for 500 spam messages and 300 legitimate messages were performed. © 2016 International Information Institute.