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“It’s shocking!": Analysing the impact and reactions to the A3: Android apps behaviour analyser
Goethe University Frankfurt, Frankfurt am Main, Germany.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0001-7384-4552
Vienna University of Business and Economics, Vienna, Austria.
Vienna University of Business and Economics, Vienna, Austria.
2018 (English)In: Data and Applications Security and Privacy XXXII / [ed] Florian Kerschbaum, Stefano Paraboschi, Basel, Switzerland: Springer, 2018, p. 198-215Conference paper, Published paper (Refereed)
Abstract [en]

The lack of privacy awareness in smartphone ecosystems prevents users from being able to compare apps in terms of privacy and from making informed privacy decisions. In this paper we analysed smartphone users’ privacy perceptions and concerns based on a novel privacy enhancing tool called Android Apps Behaviour Analyser (A3). The A3 tool enables user to behaviourally analyse the privacy aspects of their installed apps and notifies about potential privacy invasive activities. To examine the capabilities of A3 we designed a user study. We captured and contrasted privacy concern and perception of 52 participants, before and after using our tool. The results showed that A3 enables users to easily detect their smartphone app’s privacy violation activities. Further, we found that there is a significant difference between users’ privacy concern and expectation before and after using A3 and the majority of them were surprised to learn how often their installed apps access personal resources. Overall, we observed that the A3 tool was capable to influence the participants’ attitude towards protecting their privacy.

Place, publisher, year, edition, pages
Basel, Switzerland: Springer, 2018. p. 198-215
Series
Lecture Notes in Computer Science ; 10980
Keywords [en]
Android, Permission, Privacy, Privacy behaviour, Privacy concern, Smartphone ecosystems, Behavioral research, Data privacy, Ecosystems, Smartphones, Android apps, Privacy aspects, Privacy awareness, Privacy concerns, Privacy violation, Smartphone app, Android (operating system)
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-69079DOI: 10.1007/978-3-319-95729-6_13Scopus ID: 2-s2.0-85050549614ISBN: 9783319957289 (print)OAI: oai:DiVA.org:kau-69079DiVA, id: diva2:1245629
Conference
32nd Annual IFIP WG 11.3 Conference, DBSec 2018, Bergamo, Italy, July 16–18, 2018, Proceedings
Available from: 2018-09-05 Created: 2018-09-05 Last updated: 2018-11-01Bibliographically approved
In thesis
1. Advancing Models of Privacy Decision Making: Exploring the What & How of Privacy Behaviours
Open this publication in new window or tab >>Advancing Models of Privacy Decision Making: Exploring the What & How of Privacy Behaviours
2018 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

People's decisions do not happen in a vacuum; there are multiple factors that may affect them. There are external determinants, such as cost/benefit calculation of decision outcomes. There are also internal factors, such as attitudes, personality, emotions, age, and nationality. Frequently, the latter have a final say on the decision at hand, and similar determinants are triggered during the digital interaction when people make decisions about their privacy.

The current digital privacy landscape is filled with recurring security breaches and leaks of personal information collected by online service providers. Growing dependency on Internet-connected devices and increasing privacy risks prompted policy makers to protect individuals' right to privacy. In Europe, the General Data Protection Regulation requires companies to provide adequate information about their data collection and processing practices to users, to increase privacy awareness and enable better decision making. Regardless, currently there is no sufficient, usable technology, which could help people make improved privacy decisions, decreasing over-disclosure and oversharing. Hence, multidisciplinary researchers aim at developing new privacy-enhancing solutions. To define such solutions and successfully convey data provision and processing practices, potential risks, or harms resulting from information disclosure, it is crucial to understand cognitive processes underpinning privacy decisions.

In this thesis, we examine privacy decisions and define factors that influence them. We investigate the attitude-behaviour relationship and identify privacy concerns affecting perceptions of privacy. Additionally, we examine factors influencing information sharing, such as emotional arousal and personality traits. Our results demonstrate that there is a relationship between privacy concerns and behaviours, and that simplified models of behaviour are insufficient to predict privacy decisions. Our findings show that internal factors, such as nationality and culture, emotional arousal, and individual characteristics, affect privacy decisions. Based on our findings, we conclude that future models of privacy should incorporate such determinants. Further, we postulate that privacy user interfaces must become more flexible and personalised than the current solutions.

Abstract [en]

Growing dependency on Internet-connected devices and increasing privacy risks prompted policymakers to protect individuals’ right to privacy. In Europe, the General Data Protection Regulation requires companies to provide users with adequate information about data collection and processing practices to increase privacy awareness and enable better decisions. Hence, multidisciplinary researchers aim at developing new privacy-enhancing solutions. However, to develop such solutions it is crucial to understand cognitive processes underpinning privacy decisions.

This thesis objective is to investigate privacy behaviours. We identify privacy concerns affecting perceptions of privacy and examine factors influencing information sharing. We show that simplified models of behaviour are insufficient predictors of privacy decisions, and that demographic characteristic, emotion and personality affect privacy attitudes and behaviours. Based on our findings we conclude that future models of privacy and designs of privacy user interfaces must incorporate such behavioural determinants.

Place, publisher, year, edition, pages
Karlstads universitet, 2018. p. 24
Series
Karlstad University Studies, ISSN 1403-8099 ; 2018:51
Keywords
Privacy, Attitudes & Behaviour, Modelling Behaviour, HCI, UI Design
National Category
Computer and Information Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-69974 (URN)978-91-7063-891-6 (ISBN)978-91-7063-986-9 (ISBN)
Presentation
2018-12-11, Sjöströmsalen, 1B 309, Universitetsgatan 2, Karlstad, 13:15 (English)
Opponent
Supervisors
Available from: 2018-11-19 Created: 2018-10-30 Last updated: 2018-12-11Bibliographically approved

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Citation style
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