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Towards a threat assessment framework for apps collusion

Harsha Kumara Kalutarage Orcid Logo, Hoang Nguyen Orcid Logo, Siraj Shaikh Orcid Logo

Telecommunication Systems, Volume: 66, Issue: 3, Pages: 417 - 430

Swansea University Authors: Hoang Nguyen Orcid Logo, Siraj Shaikh Orcid Logo

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DOI (Published version): 10.1007/s11235-017-0296-1

Abstract

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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Published in: Telecommunication Systems
ISSN: 1018-4864 1572-9451
Published: Springer Science and Business Media LLC 2017
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URI: https://cronfa.swan.ac.uk/Record/cronfa61043
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first_indexed 2022-10-14T15:13:47Z
last_indexed 2023-01-13T19:21:36Z
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spelling 2022-12-15T16:07:50.8532118 v2 61043 2022-09-05 Towards a threat assessment framework for apps collusion cb24d5c5080534dc5b5e3390f24dd422 0000-0003-0260-1697 Hoang Nguyen Hoang Nguyen true false 50117e8faac2d0937989e14847105704 0000-0002-0726-3319 Siraj Shaikh Siraj Shaikh true false 2022-09-05 SCS 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 SecurityTM. Journal Article Telecommunication Systems 66 3 417 430 Springer Science and Business Media LLC 1018-4864 1572-9451 Android security; Apps collusion; Threat assessment; Bayesian; Statistical modelling 1 11 2017 2017-11-01 10.1007/s11235-017-0296-1 COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University This work is as a result of the App Collusion Detection (ACiD) (http://cs.swan.ac.uk/~csmarkus/ACID/) project funded by the Engineering and Physical Sciences Research Council (EPSRC) of the UK under the grant EP/L022656/1 (http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/L022656/1). 2022-12-15T16:07:50.8532118 2022-09-05T22:38:12.4967336 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Harsha Kumara Kalutarage 0000-0001-6430-9558 1 Hoang Nguyen 0000-0003-0260-1697 2 Siraj Shaikh 0000-0002-0726-3319 3 61043__25458__66862b924d45499192e782a8d2fb1aed.pdf 61043_VoR.pdf 2022-10-14T16:11:27.2334575 Output 1143684 application/pdf Version of Record true © The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License true eng http://creativecommons.org/licenses/by/4.0
title Towards a threat assessment framework for apps collusion
spellingShingle Towards a threat assessment framework for apps collusion
Hoang Nguyen
Siraj Shaikh
title_short 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_sort Towards a threat assessment framework for apps collusion
author_id_str_mv cb24d5c5080534dc5b5e3390f24dd422
50117e8faac2d0937989e14847105704
author_id_fullname_str_mv cb24d5c5080534dc5b5e3390f24dd422_***_Hoang Nguyen
50117e8faac2d0937989e14847105704_***_Siraj Shaikh
author Hoang Nguyen
Siraj Shaikh
author2 Harsha Kumara Kalutarage
Hoang Nguyen
Siraj Shaikh
format Journal article
container_title Telecommunication Systems
container_volume 66
container_issue 3
container_start_page 417
publishDate 2017
institution Swansea University
issn 1018-4864
1572-9451
doi_str_mv 10.1007/s11235-017-0296-1
publisher Springer Science and Business Media LLC
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 1
active_str 0
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 SecurityTM.
published_date 2017-11-01T04:19:38Z
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score 11.013731

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