Email Classification Using Artificial Neural Network

Samy S. Abu-Naser
North Dakota State University (PhD)
Abstract: In recent years email has become one of the fastest and most economical means of communication. However increase of email users has resulted in the dramatic increase of spam emails during the past few years. Data mining -classification algorithms are used to categorize the email as spam or non-spam. Numerous email spam messages are marketable in nature but might similarly encompass camouflaged links that seem to be for acquainted websites but actually lead to phishing web sites or sites that are holding malware. Spam email might likewise comprise malware as scripts or other executable file attachments. Spammers use spam bots to generate email distribution lists. A spammer naturally sends an email to millions of email addresses. The address and identity of the sender are concealed Mass Mailing with the expectation that only a small number will respond or interact with the message and Spam mails might be the cause of phishing attack, hacking of banking accounts, attacks on confidential data. Spamming is rising at a quick speed as sending a deluge of mails is simple and for free. Spam mails interrupt the one calmness, spending much time and put away various resources like memory and networks bandwidth. In this study, we present a method for spam filtering using Artificial Neural Network to predict whether an email is spam or not.
Keywords Classification Algorithms  Neural Networks  Spam Mails
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