SPAM AND EMAIL NOTIFICATION USING ARTIFICIAL NEURAL NETWORK ALGORITHM
M.Geethapriya1, M.Jeevanantham2, S.Raampradaap3 ,A.Saravanakumar4
1Assistant Professor, Dept of Computer Science Engineering
2,3,4 Dept of Computer Science Engineering
1,2,3,4N.S.N College of Engineering and Technology , Karur, India
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Abstract -
Email spam is operations which are sending the undesirable messages to different email client. E-mail spam is the very recent problem for every individual. The e-mail spam is nothing it’s an advertisement of any company/product or any kind of virus which is receiving by the email client mailbox without any notification. The detection of email spam involves various techniques such as rule-based filtering, content-based filtering, and machine learning algorithms. Rule-based filtering uses predefined rules to identify spam based on certain characteristics such as the sender's address, subject line, or message content. Content-based filtering analyses the content of the email, including keywords, images, and formatting, to identify spam. To solve this problem the different spam filtering technique is used. The spam filtering techniques are used to protect our mailbox for spam mails. The Artificial neural network classification with three-layer framework are used that includes obfuscator, classifier and anomaly detector for spam classification for bulk emails. The ANN is very simple and efficient method for spam classification. The real time dataset is used for classification of spam and non-spam mails. The feature extraction technique is used to extract the feature in terms of digest based on bucket classification. The result is to increase the accuracy of the system. And implement Self Acknowledgeable Intranet Mail System has been designed and implemented to benefit the sender about the status of his mail. Once a mail is sent, the sender can know the receiver activity in the mail system until the mail is viewed. Finally provide the pop-up window to identify the mail content at the time of open the spam mails.
Key Words: Big Data, Artificial Neural Network, .NET, SQL, Spam Mail
