Maximilian Häring, University of Bonn; Eva Gerlitz, Fraunhofer FKIE; Christian Tiefenau, University of Bonn; Matthew Smith, University of Bonn, Fraunhofer FKIE; Dominik Wermke and Sascha Fahl, CISPA, University of Hannover; Yasemin Acar, Max Planck Institute for Security and Privacy
To help tackle the COVID-19 pandemic, the tech community has put forward proximity detection apps to help warn people who might have been exposed to the coronavirus. The privacy implications of such apps have been discussed both in academic circles and the general population. The discussion in Germany focused on the trade-off between a centralized or decentralized approach for data collection and processing and their implications. Specifically, privacy dominated the public debate about the proposed "Corona-Warn-App." This paper presents a study with a quota sample of the German population (n=744) to assess what the population knew about the soon-to-be-released app and their willingness to use it. We also presented participants potential properties the app could have and asked them how these would affect their usage intention. Based on our findings, we discuss our participants' views on privacy and functionality, including their perception of selected centralized and decentralized features. We also examine a wide range of false beliefs and information that was not communicated successfully. Especially technical details, such as that the app would use Bluetooth, as opposed to location services, were unknown to many participants. Our results give insights on the complicated relationship of trust in the government and public communication on the population's willingness to adopt the app.
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author = {Maximilian H{\"a}ring and Eva Gerlitz and Christian Tiefenau and Matthew Smith and Dominik Wermke and Sascha Fahl and Yasemin Acar},
title = {Never ever or no matter what: Investigating Adoption Intentions and Misconceptions about the {Corona-Warn-App} in Germany},
booktitle = {Seventeenth Symposium on Usable Privacy and Security (SOUPS 2021)},
year = {2021},
isbn = {978-1-939133-25-0},
pages = {77--98},
url = {https://www.usenix.org/conference/soups2021/presentation/acar},
publisher = {USENIX Association},
month = aug
}