A Review: Artificial Neural Network is used to classify email spam using modified kernel search and history backup classifiers

Abstract

In Today's day in age it is very important for everybody to use emails for their general work, personal communication and all other means of formal and informal conversations that have to be made. But in the case of emails, it is very important that the unnecessary emails are cornered off and segmented in a different segment. This is important because most of the emails are for marketing and advertisement which contain the necessary information which can clog up the inbox and waste the time of the user. The browsers and email services provide their own separating techniques but the spammers always use different methods to spam the users because they keep on changing their techniques to trick the separating mechanism. In this area of research, many researches have provided different techniques for segregating the spam emails from the genuine ones. In past years various techniques have been used with different types of classifiers for identification of the spam emails. This proposed work will use a modified kernel based technique which will build up history backup classification model by using neural networks as the classifier for classifying the spam emails