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

BARBIE: Robust Backdoor Detection Based on Latent Separability

Hanlei Zhang (Zhejiang University), Yijie Bai (Zhejiang University), Yanjiao Chen (Zhejiang University), Zhongming Ma (Zhejiang University), Wenyuan Xu (Zhejiang University)

Read More

TWINFUZZ: Differential Testing of Video Hardware Acceleration Stacks

Matteo Leonelli (CISPA Helmholtz Center for Information Security), Addison Crump (CISPA Helmholtz Center for Information Security), Meng Wang (CISPA Helmholtz Center for Information Security), Florian Bauckholt (CISPA Helmholtz Center for Information Security), Keno Hassler (CISPA Helmholtz Center for Information Security), Ali Abbasi (CISPA Helmholtz Center for Information Security), Thorsten Holz (CISPA Helmholtz Center for Information…

Read More

Magmaw: Modality-Agnostic Adversarial Attacks on Machine Learning-Based Wireless Communication...

Jung-Woo Chang (University of California, San Diego), Ke Sun (University of California, San Diego), Nasimeh Heydaribeni (University of California, San Diego), Seira Hidano (KDDI Research, Inc.), Xinyu Zhang (University of California, San Diego), Farinaz Koushanfar (University of California, San Diego)

Read More

MingledPie: A Cluster Mingling Approach for Mitigating Preference Profiling...

Cheng Zhang (Hunan University), Yang Xu (Hunan University), Jianghao Tan (Hunan University), Jiajie An (Hunan University), Wenqiang Jin (Hunan University)

Read More