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An Integrated Model to Email Spam Classification Using an Enhanced Grasshopper Optimization Algorithm to Train a Multilayer Perceptron Neural Network

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Advances in Cyber Security (ACeS 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1347))

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Abstract

Email is an important communication that the Internet has made available. One of the significance is seen in the great ease in which immediate transmission of internet data is done during email transmission. This great ease emerges with a major issue which is the continuous increase in spam emails. Thus, the need for a spam email detector. The versatility and adaptability of the nature of spam influenced past innovations. However, previous techniques have been weakened. This study introduces an email detection model that is designed based on use of an improved version of the grasshopper optimization algorithm to train a Multilayer Perceptron in classifying emails as ham and spam. To validate the performance of EGOA, executed on the spam email dataset are utilized, then the performance was relatively compared with popular search algorithms. The implementation demonstrates that EGOA introduces the best results with high accuracy of up to 96.09%.

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Author information

Authors and Affiliations

  1. Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin, Terengganu, Malaysia

    Sanaa A. A. Ghaleb, Mumtazimah Mohamad & Engku Fadzli Hasan Syed Abdullah

  2. Faculty of Ocean Engineering Technology and Informatics, Terengganu, Malaysia

    Waheed A. H. M. Ghanem

  3. Faculty of Education-Aden and Faculty of Education-Saber, Aden University, Aden, Yemen

    Sanaa A. A. Ghaleb & Waheed A. H. M. Ghanem

  4. Faculty of Engineering, Aden University, Aden, Yemen

    Sanaa A. A. Ghaleb & Waheed A. H. M. Ghanem

Authors
  1. Sanaa A. A. Ghaleb
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  2. Mumtazimah Mohamad
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  3. Engku Fadzli Hasan Syed Abdullah
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  4. Waheed A. H. M. Ghanem
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Corresponding author

Correspondence to Sanaa A. A. Ghaleb .

Editor information

Editors and Affiliations

  1. National Advanced IPv6 Centre, Universiti Sains Malaysia, Penang, Malaysia

    Mohammed Anbar

  2. Hodeidah University, Hodeidah, Yemen

    Nibras Abdullah

  3. National Advanced IPv6 Centre, Universiti Sains Malaysia, Penang, Malaysia

    Selvakumar Manickam

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Ghaleb, S.A.A., Mohamad, M., Abdullah, E.F.H.S., Ghanem, W.A.H.M. (2021). An Integrated Model to Email Spam Classification Using an Enhanced Grasshopper Optimization Algorithm to Train a Multilayer Perceptron Neural Network. In: Anbar, M., Abdullah, N., Manickam, S. (eds) Advances in Cyber Security. ACeS 2020. Communications in Computer and Information Science, vol 1347. Springer, Singapore. https://doi.org/10.1007/978-981-33-6835-4_27

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  • DOI: https://doi.org/10.1007/978-981-33-6835-4_27

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-33-6834-7

  • Online ISBN: 978-981-33-6835-4

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