Existing research has explored the explanation of differential privacy in health contexts. Our study adapts well-performing textual descriptions of local differential privacy from prior work to a new …

René Raab (Friedrich-Alexander-Universität Erlangen-Nürnberg), Arijana Bohr (Friedrich-Alexander-Universität Erlangen-Nürnberg), Kai Klede (Friedrich-Alexander-Universität Erlangen-Nürnberg), …

Finally, we identify sensitive finance and health websites that have installed trackers that are likely configured to collect form data PII in violation of Meta and Google policies.

In this paper, we consider a common problem when analyzing health data: estimating means for different groups. We discuss a generic privacy-preserving method for approximating the means of …

In contrast to prior findings in the health context, adding an implications statement to LDP and other PET descriptions (FL, FL+LDP, and GT) only marginally improved understanding in our study, but also did …

Although these devices enable their users to monitor their activities and health, they also raise new security and privacy concerns, given the sensitive data (e.g., steps, heart rate) they collect and the …

Abstract: Through voice characteristics and manner of expression, even seemingly benign voice recordings can reveal sensitive attributes about a recorded speaker (e. g., geographical origin, health …

While being beneficial to improve security and privacy for service providers, their solution requires strong trust assumption for the (central) validation service that learns all health-related details of the users.

From tracking daily eating habits and vital functions to monitoring sleep patterns and even the menstrual cycle, these apps have become ubiquitous in their pursuit of comprehensive health insights.

This tracking including browsing and search queries performed within third-party Mini Programs, some of which manage particu- larly sensitive data; for instance, we also identified browsing data in 89.7% of …