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SMSPROTECT: An automatic smishing detection mobile application

Short Messaging Service (SMS) has grown to become the most widely used feature in mobile devices. The technological advancements that birthed other alternative messaging applications have not been able to phase out the use of the SMS. However, hackers have been exploiting this SMS feature to perpetr...

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Main Authors: Akande, O.N., Gbenle, O., Abikoye, O.C., Jimoh, R.G., Akande, H.B., Balogun, A.O., Fatokun, A.
Format: Article
Published: Korean Institute of Communication Sciences 2022
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131818173&doi=10.1016%2fj.icte.2022.05.009&partnerID=40&md5=8075749a3dc0b872735b160c5f628aa7
http://eprints.utp.edu.my/33417/
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spelling my.utp.eprints.334172022-07-26T08:46:34Z SMSPROTECT: An automatic smishing detection mobile application Akande, O.N. Gbenle, O. Abikoye, O.C. Jimoh, R.G. Akande, H.B. Balogun, A.O. Fatokun, A. Short Messaging Service (SMS) has grown to become the most widely used feature in mobile devices. The technological advancements that birthed other alternative messaging applications have not been able to phase out the use of the SMS. However, hackers have been exploiting this SMS feature to perpetrate smishing acts. Existing research has focused on how spam SMS could be detected and separated from ham messages but have not really done much at preventing the act of smishing. Therefore, this research presents a mobile application that used a rule-based SMS service to detect and prevent smishing attacks. Specifically, the developed SMS service allows the developed SMS mobile application to intercept incoming SMS to a smartphone. The intercepted messages were then forwarded through an Application Programming Interface (API) to the rule-based machine learning model. The model uses the carefully selected rules to analyze the retrieved message and asserts if it is a spam or ham. The result of the analysis is then forwarded to the mobile application through the API. However, the final decision to retain or discard the spam or ham depends on the user after receiving notification from the user. © 2022 The Author(s) Korean Institute of Communication Sciences 2022 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131818173&doi=10.1016%2fj.icte.2022.05.009&partnerID=40&md5=8075749a3dc0b872735b160c5f628aa7 Akande, O.N. and Gbenle, O. and Abikoye, O.C. and Jimoh, R.G. and Akande, H.B. and Balogun, A.O. and Fatokun, A. (2022) SMSPROTECT: An automatic smishing detection mobile application. ICT Express . http://eprints.utp.edu.my/33417/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description Short Messaging Service (SMS) has grown to become the most widely used feature in mobile devices. The technological advancements that birthed other alternative messaging applications have not been able to phase out the use of the SMS. However, hackers have been exploiting this SMS feature to perpetrate smishing acts. Existing research has focused on how spam SMS could be detected and separated from ham messages but have not really done much at preventing the act of smishing. Therefore, this research presents a mobile application that used a rule-based SMS service to detect and prevent smishing attacks. Specifically, the developed SMS service allows the developed SMS mobile application to intercept incoming SMS to a smartphone. The intercepted messages were then forwarded through an Application Programming Interface (API) to the rule-based machine learning model. The model uses the carefully selected rules to analyze the retrieved message and asserts if it is a spam or ham. The result of the analysis is then forwarded to the mobile application through the API. However, the final decision to retain or discard the spam or ham depends on the user after receiving notification from the user. © 2022 The Author(s)
format Article
author Akande, O.N.
Gbenle, O.
Abikoye, O.C.
Jimoh, R.G.
Akande, H.B.
Balogun, A.O.
Fatokun, A.
spellingShingle Akande, O.N.
Gbenle, O.
Abikoye, O.C.
Jimoh, R.G.
Akande, H.B.
Balogun, A.O.
Fatokun, A.
SMSPROTECT: An automatic smishing detection mobile application
author_facet Akande, O.N.
Gbenle, O.
Abikoye, O.C.
Jimoh, R.G.
Akande, H.B.
Balogun, A.O.
Fatokun, A.
author_sort Akande, O.N.
title SMSPROTECT: An automatic smishing detection mobile application
title_short SMSPROTECT: An automatic smishing detection mobile application
title_full SMSPROTECT: An automatic smishing detection mobile application
title_fullStr SMSPROTECT: An automatic smishing detection mobile application
title_full_unstemmed SMSPROTECT: An automatic smishing detection mobile application
title_sort smsprotect: an automatic smishing detection mobile application
publisher Korean Institute of Communication Sciences
publishDate 2022
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131818173&doi=10.1016%2fj.icte.2022.05.009&partnerID=40&md5=8075749a3dc0b872735b160c5f628aa7
http://eprints.utp.edu.my/33417/
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score 13.211869

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