576 research outputs found
The Serums Tool-Chain:Ensuring Security and Privacy of Medical Data in Smart Patient-Centric Healthcare Systems
Digital technology is permeating all aspects of human society and life. This leads to humans becoming highly dependent on digital devices, including upon digital: assistance, intelligence, and decisions. A major concern of this digital dependence is the lack of human oversight or intervention in many of the ways humans use this technology. This dependence and reliance on digital technology raises concerns in how humans trust such systems, and how to ensure digital technology behaves appropriately. This works considers recent developments and projects that combine digital technology and artificial intelligence with human society. The focus is on critical scenarios where failure of digital technology can lead to significant harm or even death. We explore how to build trust for users of digital technology in such scenarios and considering many different challenges for digital technology. The approaches applied and proposed here address user trust along many dimensions and aim to build collaborative and empowering use of digital technologies in critical aspects of human society
Towards Standardized Mobility Reports with User-Level Privacy
The importance of human mobility analyses is growing in both research and
practice, especially as applications for urban planning and mobility rely on
them. Aggregate statistics and visualizations play an essential role as
building blocks of data explorations and summary reports, the latter being
increasingly released to third parties such as municipal administrations or in
the context of citizen participation. However, such explorations already pose a
threat to privacy as they reveal potentially sensitive location information,
and thus should not be shared without further privacy measures.
There is a substantial gap between state-of-the-art research on privacy
methods and their utilization in practice. We thus conceptualize a standardized
mobility report with differential privacy guarantees and implement it as
open-source software to enable a privacy-preserving exploration of key aspects
of mobility data in an easily accessible way. Moreover, we evaluate the
benefits of limiting user contributions using three data sets relevant to
research and practice. Our results show that even a strong limit on user
contribution alters the original geospatial distribution only within a
comparatively small range, while significantly reducing the error introduced by
adding noise to achieve privacy guarantees
- …