A comparative performance evaluation of content based spam and malicious URL detection in E-mail

E-mail communication is growing rapidly. Email contains Text and URLs as content. Text can be suspicious, from undesired sender which contains un-required content and URLs may be malicious which redirects users to phishing (malicious) websites. Thus to stop such activity a spam and malicious URLs detection system is required which benefits users by removing spam content and malicious URLs in Email. We have used data mining approach like supervised classification which improves the systems accuracy and detects more amount of spam and malicious URLs.