TY  - CONF
A1  - Harborth, David
A1  - Hatamian, Majid
A1  - Tesfay, Welderufael Berhane
A1  - Rannenberg, Kai
T1  - A two-pillar approach to analyze the privacy policies and resource access behaviors of mobile augmented reality applications
T2  - 52nd Hawaii International Conference on System Sciences 2019 (HICSS 2019), Maui, Hawaii, 08-11 January 2019
N2  - Augmented reality (AR) gained much public attention since the success of Pok´emon Go in 2016. Technology companies like Apple or Google are currently focusing primarily on mobile AR (MAR) technologies, i.e. applications on mobile devices, like smartphones or tablets. Associated privacy issues have to be investigated early to foster market adoption. This is especially relevant since past research found several threats associated with the use of smartphone applications. Thus, we investigate two of the main privacy risks for MAR application users based on a sample of 19 of the most downloaded MAR applications for Android. First, we assess threats arising from bad privacy policies based on a machine-learning approach. Second, we investigate which smartphone data resources are accessed by the MAR applications. Third, we combine both approaches to evaluate whether privacy policies cover certain data accesses or not. We provide theoretical and practical implications and recommendations based on our results.
Y1  - 2018
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/54542
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-545424
SN  - 978-0-9981331-2-6
N1  - License (for files): Creative Commons Attribution 4.0 International
N1  - Später erschienen in: Proceedings of the 52nd Annual Hawaii International Conference on System Sciences, Honolulu, HI : University of Hawai'i at Manoa, [2019], S. 5029-5038, ISBN 978-0-9981331-2-6
ER  -