Leona Lassak (Ruhr University Bochum), Hanna Püschel (TU Dortmund University), Oliver D. Reithmaier (Leibniz University Hannover), Tobias Gostomzyk (TU Dortmund University), Markus Dürmuth (Leibniz University Hannover)

In times of big data, connected devices, and increasing self-measurement, protecting consumer privacy remains a challenge despite ongoing technological and legislative efforts. Data trustees present a promising solution, aiming to balance data utilization with privacy concerns by facilitating secure data sharing and ensuring individual control. However, successful implementation hinges on user acceptance and trust.

We conducted a large-scale, vignette-based, census-representative online study examining factors influencing the acceptance of data trustees for medical, automotive, IoT, and online data. With n=714 participants from Germany and n=1036 from the US, our study reveals varied willingness to use data trustees across both countries, with notable skepticism and outright rejection from a significant portion of users.

We also identified significant domain-specific differences, including the influence of user anonymity, perceived personal and societal benefits, and the recipients of the data.

Contrary to common beliefs, organizational and regulatory decisions such as the storage location, the operator, and supervision appeared less relevant to users' decisions.

In conclusion, while there exists a potential user base for data trustees, achieving widespread acceptance will require explicit and targeted implementation strategies tailored to address diverse user expectations. Our findings underscore the importance of understanding these nuances for effectively deploying data trustee frameworks that meet both regulatory requirements and user preferences while upholding highest security and privacy standards.

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Delay-allowed Differentially Private Data Stream Release

Xiaochen Li (University of Virginia), Zhan Qin (Zhejiang University), Kui Ren (Zhejiang University), Chen Gong (University of Virginia), Shuya Feng (University of Connecticut), Yuan Hong (University of Connecticut), Tianhao Wang (University of Virginia)

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DUMPLING: Fine-grained Differential JavaScript Engine Fuzzing

Liam Wachter (EPFL), Julian Gremminger (EPFL), Christian Wressnegger (Karlsruhe Institute of Technology (KIT)), Mathias Payer (EPFL), Flavio Toffalini (EPFL)

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NDSS Symposium 2025 Welcome and Opening Remarks

General Chairs: David Balenson, USC Information Sciences Institute and Heng Yin, University of California, Riverside Program Chairs: Christina Pöpper, New York University Abu Dhabi and Hamed Okhravi, MIT Lincoln Laboratory Artifact Evaluation Chairs: Daniele Cono D’Elia, Sapienza University and Mathy Vanhoef, KU Leuven

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