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How much Privilege does an App Need? Investigating Resource Usage of Android Apps
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (from 2013). (Privacy and Security, PriSec)ORCID-id: 0000-0002-5235-5335
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (from 2013). (Privacy and Security, PRISEC)ORCID-id: 0000-0001-6459-8409
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (from 2013). (Privacy and Security, PRISEC)ORCID-id: 0000-0002-0418-4121
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (from 2013).ORCID-id: 0000-0003-0778-4736
2017 (Engelska)Ingår i: Proceedings of the Fifteenth International Conference on Privacy, Security and Trust – PST 2017 (IEEE proceedings pendings), IEEE, 2017Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Arguably, one of the default solutions to many of today’s everyday errands is to install an app. In order to deliver a variety of convenient and user-centric services, apps need to access different types of information stored in mobile devices, much of which is personal information. In principle, access to such privacy sensitive data should be kept to a minimum. In this study, we focus on privilege utilization patterns by apps installed on Android devices. Though explicit consent is required prior to first time access to the resource, the unavailability of usage information makes it unclear when trying to reassess the users initial decision. On the other hand, if granted privilege with little or no usage, it would suggest the likely violation of the principle of least privilege. Our findings illustrate a plausible requirement for visualising resource usage to aid the user in their decision- making and finer access control mechanisms. 

Ort, förlag, år, upplaga, sidor
IEEE, 2017.
Nationell ämneskategori
Datavetenskap (datalogi)
Forskningsämne
Datavetenskap
Identifikatorer
URN: urn:nbn:se:kau:diva-65605DOI: 10.1109/PST.2017.00039ISI: 000447643500028ISBN: 978-1-5386-2487-6 (tryckt)ISBN: 978-1-5386-2488-3 (digital)OAI: oai:DiVA.org:kau-65605DiVA, id: diva2:1174212
Konferens
The Fifteenth International Conference on Privacy, Security and Trust – PST 2017. August 28-30, 2017 Calgary, Alberta, Canada
Tillgänglig från: 2018-01-15 Skapad: 2018-01-15 Senast uppdaterad: 2019-07-11Bibliografiskt granskad
Ingår i avhandling
1. Towards Measuring Apps' Privacy-Friendliness
Öppna denna publikation i ny flik eller fönster >>Towards Measuring Apps' Privacy-Friendliness
2018 (Engelska)Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

Today's phone could be described as a charismatic tool that has the ability to keep human beings captivated for a considerable amount of their precious time. Users remain in the illusory wonderland with free services, while their data becomes the subject to monetizing by a genie called big data. In other words, users pay with their personal data but the price is in a way invisible. Poor means to observe and to assess the consequences of data disclosure causes hindrance for the user to be aware of and to take preventive measures.

Mobile operating systems use permission-based access control mechanism to guard system resources and sensors. Depending on the type, apps require explicit consent from the user in order to avail access to those permissions. Nonetheless, it does not put any constraint on access frequency. Granted privileges allow apps to access to users' personal information for indefinite period of time until being revoked explicitly. Available control tools lack monitoring facility which undermines the performance of access control model. It has the ability to create privacy risks and nontransparent handling of personal information for the data subject.

This thesis argues that app behavior analysis yields information which has the potential to increase transparency, to enhance privacy protection, to raise awareness regarding consequences of data disclosure, and to assist the user in informed decision making while selecting apps or services. It introduces models and methods, and demonstrates the risks with experiment results. It also takes the risks into account and makes an effort to determine apps' privacy-friendliness based on empirical data from app-behavior analysis.

Abstract [en]

Today's phone could be described as a charismatic tool that has the ability to keep human beings captivated for a considerable amount of their precious time. Users remain in the illusory wonderland with free services, while their data becomes the subject to monetizing by a genie called big data. In other words, users pay with their personal data but the price is in a way invisible. They face hindrance to be aware of and to take preventive measures because of poor means to observe and to assess consequences of data disclosure. Available control tools lack monitoring properties that do not allow the user to comprehend the magnitude of personal data access. Such circumstances can create privacy risks, erode intervenability of access control mechanism and lead to opaque handling of personal information for the data subject.

This thesis argues that app behavior analysis yields information which has the potential to increase transparency, to enhance privacy protection, to raise awareness regarding consequences of data disclosure, and to assist the user in informed decision making while selecting apps or services. It introduces models and methods, and demonstrates the data disclosure risks with experimental results. It also takes the risks into account and makes an effort to determine apps' privacy-friendliness based on empirical data from app-behavior analysis.

Ort, förlag, år, upplaga, sidor
Karlstad: Karlstads universitet, 2018. s. 27
Serie
Karlstad University Studies, ISSN 1403-8099 ; 2018:31
Nyckelord
Mobile OS, Apps, User data, Transparency, Privacy
Nationell ämneskategori
Datavetenskap (datalogi)
Forskningsämne
Datavetenskap
Identifikatorer
urn:nbn:se:kau:diva-68569 (URN)978-91-7063-864-0 (ISBN)978-91-7063-959-3 (ISBN)
Presentation
2018-09-07, 1D 222, Universitetsgatan 2, Karlstad, 10:15 (Engelska)
Opponent
Handledare
Tillgänglig från: 2018-08-17 Skapad: 2018-07-23 Senast uppdaterad: 2019-07-11Bibliografiskt granskad

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Momen, NurulPulls, TobiasFritsch, LotharLindskog, Stefan

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Momen, NurulPulls, TobiasFritsch, LotharLindskog, Stefan
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Institutionen för matematik och datavetenskap (from 2013)
Datavetenskap (datalogi)

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Totalt: 266 träffar
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