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Towards a threat assessment framework for apps collusion

App collusion refers to two or more apps working together to achieve a malicious goal that they otherwise would not be able to achieve individually. The permissions based security model of Android does not address this threat as it is rather limited to mitigating risks of individual apps. This paper...

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Detalles Bibliográficos
Autores principales: Kalutarage, Harsha Kumara, Nguyen, Hoang Nga, Shaikh, Siraj Ahmed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6961490/
https://www.ncbi.nlm.nih.gov/pubmed/32009772
http://dx.doi.org/10.1007/s11235-017-0296-1
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author Kalutarage, Harsha Kumara
Nguyen, Hoang Nga
Shaikh, Siraj Ahmed
author_facet Kalutarage, Harsha Kumara
Nguyen, Hoang Nga
Shaikh, Siraj Ahmed
author_sort Kalutarage, Harsha Kumara
collection PubMed
description App collusion refers to two or more apps working together to achieve a malicious goal that they otherwise would not be able to achieve individually. The permissions based security model of Android does not address this threat as it is rather limited to mitigating risks of individual apps. This paper presents a technique for quantifying the collusion threat, essentially the first step towards assessing the collusion risk. The proposed method is useful in finding the collusion candidate of interest which is critical given the high volume of Android apps available. We present our empirical analysis using a classified corpus of over 29,000 Android apps provided by Intel Security(TM).
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spelling pubmed-69614902020-01-29 Towards a threat assessment framework for apps collusion Kalutarage, Harsha Kumara Nguyen, Hoang Nga Shaikh, Siraj Ahmed Telecommun Syst Article App collusion refers to two or more apps working together to achieve a malicious goal that they otherwise would not be able to achieve individually. The permissions based security model of Android does not address this threat as it is rather limited to mitigating risks of individual apps. This paper presents a technique for quantifying the collusion threat, essentially the first step towards assessing the collusion risk. The proposed method is useful in finding the collusion candidate of interest which is critical given the high volume of Android apps available. We present our empirical analysis using a classified corpus of over 29,000 Android apps provided by Intel Security(TM). Springer US 2017-03-07 2017 /pmc/articles/PMC6961490/ /pubmed/32009772 http://dx.doi.org/10.1007/s11235-017-0296-1 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Kalutarage, Harsha Kumara
Nguyen, Hoang Nga
Shaikh, Siraj Ahmed
Towards a threat assessment framework for apps collusion
title Towards a threat assessment framework for apps collusion
title_full Towards a threat assessment framework for apps collusion
title_fullStr Towards a threat assessment framework for apps collusion
title_full_unstemmed Towards a threat assessment framework for apps collusion
title_short Towards a threat assessment framework for apps collusion
title_sort towards a threat assessment framework for apps collusion
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6961490/
https://www.ncbi.nlm.nih.gov/pubmed/32009772
http://dx.doi.org/10.1007/s11235-017-0296-1
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