Privacy at a Glance: The User-Centric Design of Glanceable Data Exposure Visualizations
| Autor: | Arwa Alsubhi, Jessica Qiu, Bart P. Knijnenburg, Moses Namara, Paritosh Bahirat, Daricia Wilkinson, Pamela Wisniewski, Jing Lyu |
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| Rok vydání: | 2020 |
| Předmět: |
Ethics
Computer science business.industry design Information technology 020207 software engineering mobile QA75.5-76.95 02 engineering and technology privacy BJ1-1725 Human–computer interaction Electronic computers. Computer science 020204 information systems qualitative 0202 electrical engineering electronic engineering information engineering General Earth and Planetary Sciences user business General Environmental Science User-centered design |
| Zdroj: | Proceedings on Privacy Enhancing Technologies, Vol 2020, Iss 2, Pp 416-435 (2020) |
| ISSN: | 2299-0984 |
| DOI: | 10.2478/popets-2020-0034 |
| Popis: | Smartphone users are often unaware of mobile applications’ (“apps”) third-party data collection and sharing practices, which put them at higher risk of privacy breaches. One way to raise awareness of these practices is by providing unobtrusive but pervasive visualizations that can be presented in a glanceable manner. In this paper, we applied Wogalter et al.’s Communication-Human Information Processing model (C-HIP) to design and prototype eight different visualizations that depict smartphone apps’ data sharing activities. We varied the granularity and type (i.e., data-centric or app-centric) of information shown to users and used the screensaver/lock screen as a design probe. Through interview-based design probes with Android users (n=15), we investigated the aspects of the data exposure visualizations that influenced users’ comprehension and privacy awareness. Our results shed light on how users’ perceptions of privacy boundaries influence their preference regarding the information structure of these visualizations, and the tensions that exist in these visualizations between glanceability and granularity. We discuss how a pervasive, soft paternalistic approach to privacy-related visualization may raise awareness by enhancing the transparency of information flow, thereby, unobtrusively increasing users’ understanding of data sharing practices of mobile apps. We also discuss implications for privacy research and glanceable security. |
| Databáze: | OpenAIRE |
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