"Am I Private and If So, how Many?" - Communicating Privacy Guarantees of Differential Privacy with Risk Communication Formats
Daniel Franzen (1), Saskia Nu\~nez von Voigt (2), Peter S\"orries (1),, Florian Tschorsch (2), Claudia M\"uller-Birn (1) ((1) Freie Universit\"at, Berlin, (2) Technische Universit\"at Berlin)

TL;DR
This paper introduces a novel method for communicating differential privacy guarantees using risk communication formats from medicine, evaluated through a crowd-sourced study to assess understanding and confidence in privacy risk information.
Contribution
It proposes a new approach to effectively communicate differential privacy guarantees using quantitative risk notifications based on medical communication formats.
Findings
Notifications conveyed privacy risk information as effectively as qualitative methods.
Participants with low numeracy were overconfident in their understanding.
Notifications reduced confidence in understanding compared to qualitative notifications.
Abstract
Decisions about sharing personal information are not trivial, since there are many legitimate and important purposes for such data collection, but often the collected data can reveal sensitive information about individuals. Privacy-preserving technologies, such as differential privacy (DP), can be employed to protect the privacy of individuals and, furthermore, provide mathematically sound guarantees on the maximum privacy risk. However, they can only support informed privacy decisions, if individuals understand the provided privacy guarantees. This article proposes a novel approach for communicating privacy guarantees to support individuals in their privacy decisions when sharing data. For this, we adopt risk communication formats from the medical domain in conjunction with a model for privacy guarantees of DP to create quantitative privacy risk notifications. We conducted a…
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Taxonomy
TopicsPrivacy, Security, and Data Protection · Privacy-Preserving Technologies in Data · Data-Driven Disease Surveillance
