Review on Effective Email Classification for Spam and Non Spam Detection on Various Machine Learning Techniques

Some time email receiver or user receives a email which he does not intended to receive or accept, these kind of emails are nothing but spam emails. In other words the unsolicited bulk email is nothing but the spam. Numbers of emails users are increasing day by day, email users communicate around the world using email and internet. Now days a large volumes of spam emails are causing serious problem for Internet service and Internet users. This affects or degrades user search experience, which assists propagation of virus in network or grid, this will increases load on traffic in the network. It also wastes valuable time of user, user’s energy for appropriate emails among the spam emails. To avoiding such spam there are so many traditional anti spam techniques includes, rule based system, White list and DNS black holes, IP blacklist, Heuristic based filter, Bayesian based filters. All these techniques are based on links of the mail or content of the email. In this paper, we conferred our study on various existing techniques on spam detection and finding the effective, accurate, and reliable spam detection technique. DOI: 10.17762/ijritcc2321-8169.150315