Botnet Spam E-Mail Detection Using Deep Recurrent Neural Network
Mohammad Alauthman · International Journal of Emerging Trends in Engineering Research · 2020
The significant amount of SPAM emails that are derived from various botnets worldwide affect the limited capacity of mailboxes.They affect the security of personal mail and the space-loss from the communication.They affect the time required for identifying spam emails and addressing them.Till today, the email spam detection is still considered a challenging process.That is because the email spam is still happening a lot.It is because the detection still needs much improvement.Therefore, the researcher of this study develops a Gated Recurrent Unit Recurrent Neural Network (GRU-RNN) with SVM for Bot Spam email detection.The developed approach got tested by employing the Spambase dataset.The approach shows an accuracy of 98.7%.Through conducting extensive experiments, the researcher concludes that the proposed approach shows an excellent capability of detecting spam email.