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Towards Improving Privacy Awareness Regarding Apps' Permissions
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0002-5235-5335
Tech Univ Berlin, Berlin, Germany.
2017 (English)In: ICDS 2017: THE ELEVENTH INTERNATIONAL CONFERENCE ON DIGITAL SOCIETY / [ed] Berntzen, L; GersbeckSchierholz, B, International Academy, Research and Industry Association (IARIA), 2017, p. 18-23Conference paper, Published paper (Other academic)
Abstract [en]

Empirical studies show that the flow of personal information through mobile apps made devices vulnerable in terms of privacy. Cumbersome and inconvenient representation of privacy notice encourages the user to ignore it and disclose sensitive private information unintentionally. Hence, summarized permissions are presented on mobile devices and users tend to overlook them as well. Rigid structure for using a service and inherited behavior from desktop applications to accept everything are the reasons behind compelling the user to proceed without paying any attention. Complex permission based structure is also a major impediment for consumers that makes it difficult to perceive appropriate consequences of their decisions. We argue that as privacy strongly depends on individual perception, the key to educate and empower users is to providing them with transparency of what is happening on their smartphones. In consequence we suggest a convenient, transparent and proactive approach to help in understanding and deciding upon privacy implications of apps. We propose a scale that has scalability within itself. We implement this method within a tool, named Aware, that presents the summary of what applications are installed on a smartphone, which resources they access, and what are the reasons for that. Moreover, the tool is capable of nudging the user when certain sensitive data is accessed.

Place, publisher, year, edition, pages
International Academy, Research and Industry Association (IARIA), 2017. p. 18-23
Keywords [en]
Mobile Operating Systems; Mobile Phone Privacy; Control and Management of Privacy
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-66716ISI: 000426494400005ISBN: 978-1-61208-537-1 (print)OAI: oai:DiVA.org:kau-66716DiVA, id: diva2:1190716
Conference
11th International Conference on Digital Society (ICDS, Nice,France, March 19-23, 2017
Available from: 2018-03-15 Created: 2018-03-15 Last updated: 2018-10-11Bibliographically approved
In thesis
1. Towards Measuring Apps' Privacy-Friendliness
Open this publication in new window or tab >>Towards Measuring Apps' Privacy-Friendliness
2018 (English)Licentiate thesis, comprehensive summary (Other academic)
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.

Place, publisher, year, edition, pages
Karlstad: Karlstads universitet, 2018. p. 27
Series
Karlstad University Studies, ISSN 1403-8099 ; 2018:31
Keywords
Mobile OS, Apps, User data, Transparency, Privacy
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
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 (English)
Opponent
Supervisors
Available from: 2018-08-17 Created: 2018-07-23 Last updated: 2018-10-19Bibliographically approved

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
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  • de-DE
  • en-GB
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  • Other locale
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Output format
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  • asciidoc
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