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.

View More Papers

EMIRIS: Eavesdropping on Iris Information via Electromagnetic Side Channel

Wenhao Li (Shandong University), Jiahao Wang (Shandong University), Guoming Zhang (Shandong University), Yanni Yang (Shandong University), Riccardo Spolaor (Shandong University), Xiuzhen Cheng (Shandong University), Pengfei Hu (Shandong University)

Read More

LLM-xApp: A Large Language Model Empowered Radio Resource Management...

Xingqi Wu (University of Michigan-Dearborn), Junaid Farooq (University of Michigan-Dearborn), Yuhui Wang (University of Michigan-Dearborn), Juntao Chen (Fordham University)

Read More

DLBox: New Model Training Framework for Protecting Training Data

Jaewon Hur (Seoul National University), Juheon Yi (Nokia Bell Labs, Cambridge, UK), Cheolwoo Myung (Seoul National University), Sangyun Kim (Seoul National University), Youngki Lee (Seoul National University), Byoungyoung Lee (Seoul National University)

Read More