Detecting false messages in the smartphone fault reporting system

The emergence of the Internet of Things (IoT) in Smart City allows mobile application developers to develop reporting services with an aim for local citizens to interact with municipalities regarding city issues in an efficient manner. However, the credibility of the messages sent rise as a great ch...

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Main Authors: Rajoo, Sharmiladevi, Magalingam, Pritheega, Samy, Ganthan Narayana, Maarop, Nurazean, Idris, Norbik Bashah, Shanmugam, Bharanidharan, Perumal, Sundaresan
Other Authors: Saeed, Faisal
Format: Proceeding Paper
Language:English
English
English
Published: Springer 2020
Subjects:
Online Access:http://irep.iium.edu.my/75240/
http://irep.iium.edu.my/75240/1/75240_Detecting%20false%20messages%20in%20the%20smartphone_MYRA.pdf
http://irep.iium.edu.my/75240/2/75240_Detecting%20false%20messages%20in%20the%20smartphone_SCOPUS.pdf
http://irep.iium.edu.my/75240/13/75240_Detecting.pdf
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author Rajoo, Sharmiladevi
Magalingam, Pritheega
Samy, Ganthan Narayana
Maarop, Nurazean
Idris, Norbik Bashah
Shanmugam, Bharanidharan
Perumal, Sundaresan
author2 Saeed, Faisal
author_facet Saeed, Faisal
Rajoo, Sharmiladevi
Magalingam, Pritheega
Samy, Ganthan Narayana
Maarop, Nurazean
Idris, Norbik Bashah
Shanmugam, Bharanidharan
Perumal, Sundaresan
author_sort Rajoo, Sharmiladevi
building IIUM Repository
collection Online Access
description The emergence of the Internet of Things (IoT) in Smart City allows mobile application developers to develop reporting services with an aim for local citizens to interact with municipalities regarding city issues in an efficient manner. However, the credibility of the messages sent rise as a great challenge when users intentionally send false reports through the application. In this research, an evidence detection framework is developed and divided into three parts that are a data source, IoT device’s false text classification engine and output. Text-oriented digital evidence from an IoT mobile reporting service is analyzed to identify suitable text classifier and to build this framework. The Agile model that consists of define, design, build and test is used for the development of the false text classification engine. Focus given on text-based data that does not include encrypted messages. Our proposed framework able to achieve 97% of accuracy and showed the highest detection rate using SVM compared to other classifiers. The result shows that the proposed framework is able to aid digital forensic evidence experts in their initial investigation on detecting false report of a mobile reporting service application in the IoT environment.
first_indexed 2025-11-14T17:35:17Z
format Proceeding Paper
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institution International Islamic University Malaysia
institution_category Local University
language English
English
English
last_indexed 2025-11-14T17:35:17Z
publishDate 2020
publisher Springer
recordtype eprints
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spelling iium-752402020-12-29T08:48:49Z http://irep.iium.edu.my/75240/ Detecting false messages in the smartphone fault reporting system Rajoo, Sharmiladevi Magalingam, Pritheega Samy, Ganthan Narayana Maarop, Nurazean Idris, Norbik Bashah Shanmugam, Bharanidharan Perumal, Sundaresan T Technology (General) T10.5 Communication of technical information The emergence of the Internet of Things (IoT) in Smart City allows mobile application developers to develop reporting services with an aim for local citizens to interact with municipalities regarding city issues in an efficient manner. However, the credibility of the messages sent rise as a great challenge when users intentionally send false reports through the application. In this research, an evidence detection framework is developed and divided into three parts that are a data source, IoT device’s false text classification engine and output. Text-oriented digital evidence from an IoT mobile reporting service is analyzed to identify suitable text classifier and to build this framework. The Agile model that consists of define, design, build and test is used for the development of the false text classification engine. Focus given on text-based data that does not include encrypted messages. Our proposed framework able to achieve 97% of accuracy and showed the highest detection rate using SVM compared to other classifiers. The result shows that the proposed framework is able to aid digital forensic evidence experts in their initial investigation on detecting false report of a mobile reporting service application in the IoT environment. Springer Saeed, Faisal Mohammed, Fathey Gazem, Nadhmi , 2020 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/75240/1/75240_Detecting%20false%20messages%20in%20the%20smartphone_MYRA.pdf application/pdf en http://irep.iium.edu.my/75240/2/75240_Detecting%20false%20messages%20in%20the%20smartphone_SCOPUS.pdf application/pdf en http://irep.iium.edu.my/75240/13/75240_Detecting.pdf Rajoo, Sharmiladevi and Magalingam, Pritheega and Samy, Ganthan Narayana and Maarop, Nurazean and Idris, Norbik Bashah and Shanmugam, Bharanidharan and Perumal, Sundaresan (2020) Detecting false messages in the smartphone fault reporting system. In: 4th International Conference of Reliable Information and Communication Technology (IRCT 2019), 22nd-23rd September 2019, Johor. https://link.springer.com/chapter/10.1007/978-3-030-33582-3_71 10.1007/978-3-030-33582-3_71
spellingShingle T Technology (General)
T10.5 Communication of technical information
Rajoo, Sharmiladevi
Magalingam, Pritheega
Samy, Ganthan Narayana
Maarop, Nurazean
Idris, Norbik Bashah
Shanmugam, Bharanidharan
Perumal, Sundaresan
Detecting false messages in the smartphone fault reporting system
title Detecting false messages in the smartphone fault reporting system
title_full Detecting false messages in the smartphone fault reporting system
title_fullStr Detecting false messages in the smartphone fault reporting system
title_full_unstemmed Detecting false messages in the smartphone fault reporting system
title_short Detecting false messages in the smartphone fault reporting system
title_sort detecting false messages in the smartphone fault reporting system
topic T Technology (General)
T10.5 Communication of technical information
url http://irep.iium.edu.my/75240/
http://irep.iium.edu.my/75240/
http://irep.iium.edu.my/75240/
http://irep.iium.edu.my/75240/1/75240_Detecting%20false%20messages%20in%20the%20smartphone_MYRA.pdf
http://irep.iium.edu.my/75240/2/75240_Detecting%20false%20messages%20in%20the%20smartphone_SCOPUS.pdf
http://irep.iium.edu.my/75240/13/75240_Detecting.pdf