Shikun Zhang, Norman Sadeh (Carnegie Mellon University)

Inspired by earlier academic research, iOS app privacy labels and the recent Google Play data safety labels have been introduced as a way to systematically present users with concise summaries of an app’s data practices. Yet, little research has been conducted to determine how well today’s mobile app privacy labels address people’s actual privacy concerns or questions. We analyze a crowd-sourced corpus of privacy questions collected from mobile app users to determine to what extent these mobile app labels actually address users’ privacy concerns and questions. While there are differences between iOS labels and Google Play labels, our results indicate that an important percentage of people’s privacy questions are not answered or only partially addressed in today’s labels. Findings from this work not only shed light on the additional fields that would need to be included in mobile app privacy labels but can also help inform refinements to existing labels to better address users’ typical privacy questions.

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Kostas Drakonakis (FORTH), Sotiris Ioannidis (Technical University of Crete), Jason Polakis (University of Illinois at Chicago)

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Welcome to USEC

Mary Theofanos and Yasemin Acar

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Trellis: Robust and Scalable Metadata-private Anonymous Broadcast

Simon Langowski (Massachusetts Institute of Technology), Sacha Servan-Schreiber (Massachusetts Institute of Technology), Srinivas Devadas (Massachusetts Institute of Technology)

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An OS-agnostic Approach to Memory Forensics

Andrea Oliveri (EURECOM), Matteo Dell'Amico (University of Genoa), Davide Balzarotti (EURECOM)

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