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2017 | OriginalPaper | Buchkapitel

Towards Filtering of SMS Spam Messages Using Machine Learning Based Technique

verfasst von : Neelam Choudhary, Ankit Kumar Jain

Erschienen in: Advanced Informatics for Computing Research

Verlag: Springer Singapore

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Abstract

The popularity of mobile devices is increasing day by day as they provide a large variety of services by reducing the cost of services. Short Message Service (SMS) is considered one of the widely used communication service. However, this has led to an increase in mobile devices attacks like SMS Spam. In this paper, we present a novel approach that can detect and filter the spam messages using machine learning classification algorithms. We study the characteristics of spam messages in depth and then found ten features, which can efficiently filter SMS spam messages from ham messages. Our proposed approach achieved 96.5% true positive rate and 1.02% false positive rate for Random Forest classification algorithm.

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Titel: Towards Filtering of SMS Spam Messages Using Machine Learning Based Technique
verfasst von: Neelam Choudhary
Ankit Kumar Jain
Verlag: Springer Singapore
Buch: Advanced Informatics for Computing Research
Print ISBN: 978-981-10-5779-3

Electronic ISBN: 978-981-10-5780-9

Copyright-Jahr: 2017
DOI: https://doi.org/10.1007/978-981-10-5780-9_2

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