@inproceedings{10.1145/3565066.3609737,
author = {Bemmann, Florian},
title = {User-Centered Privacy to Improve User Quantification Using Smartphone Sensing},
year = {2023},
isbn = {9781450399241},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi-org.emedien.ub.uni-muenchen.de/10.1145/3565066.3609737},
doi = {10.1145/3565066.3609737},
abstract = {Mobile sensing technologies enable adaptive and context-aware applications. At the same time, they raise a range of privacy concerns. Thus, to reduce privacy concerns today apps are restricted from accessing certain information hindering to deliver full personalization and novel adaptive use cases. I investigate this issue by shedding light on the privacy concerns that arise from state-of-the-art mobile sensing data, studying the users’ perspective on mobile smartphone privacy, and proposing concepts that protect the users’ privacy while keeping the resulting data usable. I found that there is a lack of user-centered privacy design and that control features play a key role to give the users more agency. My results motivate the proliferation of control-enhancing privacy features in mobile applications. I show that the benefits of trust and system adoption surpass any impairments that control features might bring to the data.},
booktitle = {Proceedings of the 25th International Conference on Mobile Human-Computer Interaction},
articleno = {42},
numpages = {4},
keywords = {human computer interaction},
location = {Athens, Greece},
series = {MobileHCI '23 Companion}
}