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Implementation of ‘Smishing Detector’: An Efficient Model for Smishing Detection Using Neural Network

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Abstract

Neural network creates a neuron-based network similar to the human nervous system to solve classification problems efficiently. The smishing problem is a binary classification problem in which attackers target smartphone users through text messages. As smishing is a remarkable cybersecurity issue that is troubling researchers and smartphone users these days. Addressing this security issue using the most efficient algorithm is the need of the hour. This manuscript presented an algorithm for the model proposed by authors in ‘Smishing Detector’ model and implemented it using Neural Network. The result obtained proves that the neural network is much efficient in detecting smishing problem. Neural Network outperformed other machine learning algorithms with a difference of 1.11%. Neural Network performed with the final accuracy of 97.40%. In this paper, system extracted the most efficient features of smishing SMS (Short Message Service) using the Neural Network. This manuscript also reported the accuracy shown by the system for each feature selected and implemented. It is evident from the implementation that each feature selected is most effective in smishing detection and URL (Uniform Resource Locator) feature is the most effective feature with an accuracy of 94%.

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Data Availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Authors and Affiliations

Authors

Contributions

SM: conceptualization, methodology, software, data curation, writing—original draft, visualization, and investigation. DS: conceptualization, supervision, validation, and writing—review and editing.

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Correspondence to Sandhya Mishra.

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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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This article is part of the topical collection “Advances in Computational Approaches for Artificial Intelligence, Image Processing, IoT and Cloud Applications” guest-edited by Bhanu Prakash K N and M. Shivakumar.

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Mishra, S., Soni, D. Implementation of ‘Smishing Detector’: An Efficient Model for Smishing Detection Using Neural Network. SN COMPUT. SCI. 3, 189 (2022). https://doi.org/10.1007/s42979-022-01078-0

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