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iOS mobile malware analysis: a state-of-the-art

In earlier years, most malware attacks were against Android smartphones. Unfortunately, for the past few years, the trend has shifted towards attacks against the Apple iOS smartphone. Consequently, an in-depth analysis of the malware and iOS architecture is important to identify the best mitigation...

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Detalles Bibliográficos
Autores principales: Mohd Saudi, Madihah, Husainiamer, Muhammad Afif, Ahmad, Azuan, Idris, Mohd Yamani Idna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Paris 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10193328/
http://dx.doi.org/10.1007/s11416-023-00477-y
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author Mohd Saudi, Madihah
Husainiamer, Muhammad Afif
Ahmad, Azuan
Idris, Mohd Yamani Idna
author_facet Mohd Saudi, Madihah
Husainiamer, Muhammad Afif
Ahmad, Azuan
Idris, Mohd Yamani Idna
author_sort Mohd Saudi, Madihah
collection PubMed
description In earlier years, most malware attacks were against Android smartphones. Unfortunately, for the past few years, the trend has shifted towards attacks against the Apple iOS smartphone. Consequently, an in-depth analysis of the malware and iOS architecture is important to identify the best mitigation solution against malware exploitation. Hence, this paper presents a state-of-the-art deep analysis of malware against iOS smartphones. This includes comprehensive studies of malware architecture involving payload, propagation, operating algorithm, infection, and activation with underlying integration with a phylogenetic concept. Phylogenetic, borrowed from the biology field, can identify any evolution of the origin of the malware involved. To support this deep analysis of malware, a preliminary study was conducted using 12 malware samples, by focusing on social media and online banking. This took place in a controlled laboratory using hybrid analysis. The result showed that there is a way to identify the evolution of malware and as a result, a model has been developed. Based on the evaluation, 4% of mobile applications matched the patterns developed in this model. This proves that the model developed in this paper can detect any possible security exploitation related to social media and online banking for iOS mobile applications. This work can be used as guidance for other researchers working on similar interests in the future.
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spelling pubmed-101933282023-05-19 iOS mobile malware analysis: a state-of-the-art Mohd Saudi, Madihah Husainiamer, Muhammad Afif Ahmad, Azuan Idris, Mohd Yamani Idna J Comput Virol Hack Tech Original Paper In earlier years, most malware attacks were against Android smartphones. Unfortunately, for the past few years, the trend has shifted towards attacks against the Apple iOS smartphone. Consequently, an in-depth analysis of the malware and iOS architecture is important to identify the best mitigation solution against malware exploitation. Hence, this paper presents a state-of-the-art deep analysis of malware against iOS smartphones. This includes comprehensive studies of malware architecture involving payload, propagation, operating algorithm, infection, and activation with underlying integration with a phylogenetic concept. Phylogenetic, borrowed from the biology field, can identify any evolution of the origin of the malware involved. To support this deep analysis of malware, a preliminary study was conducted using 12 malware samples, by focusing on social media and online banking. This took place in a controlled laboratory using hybrid analysis. The result showed that there is a way to identify the evolution of malware and as a result, a model has been developed. Based on the evaluation, 4% of mobile applications matched the patterns developed in this model. This proves that the model developed in this paper can detect any possible security exploitation related to social media and online banking for iOS mobile applications. This work can be used as guidance for other researchers working on similar interests in the future. Springer Paris 2023-05-18 /pmc/articles/PMC10193328/ http://dx.doi.org/10.1007/s11416-023-00477-y Text en © The Author(s), under exclusive licence to Springer-Verlag France SAS, part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Paper
Mohd Saudi, Madihah
Husainiamer, Muhammad Afif
Ahmad, Azuan
Idris, Mohd Yamani Idna
iOS mobile malware analysis: a state-of-the-art
title iOS mobile malware analysis: a state-of-the-art
title_full iOS mobile malware analysis: a state-of-the-art
title_fullStr iOS mobile malware analysis: a state-of-the-art
title_full_unstemmed iOS mobile malware analysis: a state-of-the-art
title_short iOS mobile malware analysis: a state-of-the-art
title_sort ios mobile malware analysis: a state-of-the-art
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10193328/
http://dx.doi.org/10.1007/s11416-023-00477-y
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