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A Multilateral Privacy Impact Analysis Method for Android Apps
Goethe University Frankfurt, Germany.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (Prisec, Privacy and Security)ORCID iD: 0000-0002-5235-5335
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (Prisec, Privacy and Security)ORCID iD: 0000-0002-0418-4121
Goethe University Frankfurt, Germany.
2019 (English)In: Privacy Technologies and Policy / [ed] M. Naldi, G. F. Italiano, K. Rannenberg, M. Medina & A. Bourka, Cham: Springer, 2019, Vol. 11498, p. 87-106Conference paper, Published paper (Refereed)
Abstract [en]

Smartphone apps have the power to monitor most of people’s private lives. Apps can permeate private spaces, access and map social relationships, monitor whereabouts and chart people’s activities in digital and/or real world. We are therefore interested in how much information a particular app can and intends to retrieve in a smartphone. Privacy-friendliness of smartphone apps is typically measured based on single-source analyses, which in turn, does not provide a comprehensive measurement regarding the actual privacy risks of apps. This paper presents a multi-source method for privacy analysis and data extraction transparency of Android apps. We describe how we generate several data sets derived from privacy policies, app manifestos, user reviews and actual app profiling at run time. To evaluate our method, we present results from a case study carried out on ten popular fitness and exercise apps. Our results revealed interesting differences concerning the potential privacy impact of apps, with some of the apps in the test set violating critical privacy principles. The result of the case study shows large differences that can help make relevant app choices.

Place, publisher, year, edition, pages
Cham: Springer, 2019. Vol. 11498, p. 87-106
Series
Lecture Notes in Computer Science, LNCS, ISSN 0302-9743, E-ISSN 1611-3349
Keywords [en]
Smartphone apps Case study Security Privacy Android Privacy policy Reviews Privacy impact Privacy score and ranking Privacy risk Transparency
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-72432DOI: 10.1007/978-3-030-21752-5_7Scopus ID: 2-s2.0-85067825202ISBN: 978-3-030-21751-8 (print)ISBN: 978-3-030-21752-5 (electronic)OAI: oai:DiVA.org:kau-72432DiVA, id: diva2:1323331
Conference
Annual Privacy Forum 2019, Rome, Italy, June 13-14
Projects
Excellenta miljön, 8730Alert, 5617Privacy & Us, 4961Available from: 2019-06-12 Created: 2019-06-12 Last updated: 2019-07-11Bibliographically approved

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Citation style
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