Decision Making by Applying Machine Learning Techniques to Mitigate Spam SMS Attacks

Conference paper


Abou-Grad, H., Chakhar, S. and Abubahia, A. 2023. Decision Making by Applying Machine Learning Techniques to Mitigate Spam SMS Attacks. 4th International Conference on Deep Learning, Artificial Intelligence and Robotics, (ICDLAIR) 2022. Salerno, Italy 14 - 21 Dec 2022 Springer, Cham. https://doi.org/10.1007/978-3-031-30396-8_14
AuthorsAbou-Grad, H., Chakhar, S. and Abubahia, A.
TypeConference paper
Abstract

Due to exponential developments in communication networks and computer technologies, spammers have more options and tools to deliver their spam SMS attacks. This makes spam mitigation seen as one of the most active research areas in recent years. Spams also affect people’s privacy and cause revenue loss. Thus, tools for making accurate decisions about whether spam or not are needed. In this paper, a spam mitigation model is proposed to find spam from non-spam and the different processes used to mitigate spam SMS attacks. Also, anti-spam measures are applied to classify spam with the aim to have high classification accuracy performance using different classification methods. This paper seeks to apply the most appropriate machine learning (ML) techniques using decision-making paradigms to produce a ML model for mitigating spam attacks. The proposed model combines ML techniques and the Delphi method along with Agile to formulate the solution model. Also, three ML classifiers were used to cluster the dataset, which are Naive Bayes, Random Forests, and Support Vector Machine. These ML techniques are renowned as easy to apply, efficient and more accurate in comparison with other classifiers. The findings indicated that the number of clusters combined with the number of attributes has revealed a significant influence on the classification accuracy performance.

Year2023
Conference4th International Conference on Deep Learning, Artificial Intelligence and Robotics, (ICDLAIR) 2022
PublisherSpringer, Cham
Accepted author manuscript
License
File Access Level
Anyone
Publication dates
Online16 Apr 2023
Print18 Apr 2023
Publication process dates
Deposited09 May 2023
Journal citationpp. 154-166
ISSN2367-3370
Book titleKey Digital Trends in Artificial Intelligence and Robotics: Proceedings of 4th International Conference on Deep Learning, Artificial Intelligence and Robotics, (ICDLAIR) 2022
Book editorTroiano, L.
Vaccaro, A.
Kesswani, N.
Díaz-Rodriguez, I.
Brigui, I.
Pastor-Escuredo, D.
ISBN9783031303951
9783031303968
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-031-30396-8_14
Web address (URL) of conference proceedingshttps://icdlair2022.iaasse.org/sessions.html
Copyright holder© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
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Accepted author manuscript
HA_SC_AA-FullPaper-ICDLAIR-Conference2022.pdf
License: Springer Nature terms of use for archived author accepted manuscripts (AAMs) of subscription articles, books and chapters
File access level: Anyone

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