Usable Differential Privacy for the Internet-of-Things
Title | Usable Differential Privacy for the Internet-of-Things |
Publication Type | Conference Paper |
Year of Publication | 2021 |
Authors | Kühtreiber, Patrick, Reinhardt, Delphine |
Conference Name | 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) |
Date Published | March 2021 |
Publisher | IEEE |
ISBN Number | 978-1-6654-0424-2 |
Keywords | composability, Conferences, Data visualization, Differential privacy, Human Behavior, Pervasive computing, privacy, pubcrawl, resilience, Resiliency, Scalability, usable privacy |
Abstract | Current implementations of Differential Privacy (DP) focus primarily on the privacy of the data release. The planned thesis will investigate steps towards a user-centric approach of DP in the scope of the Internet-of-Things (IoT) which focuses on data subjects, IoT developers, and data analysts. We will conduct user studies to find out more about the often conflicting interests of the involved parties and the encountered challenges. Furthermore, a technical solution will be developed to assist data subjects and analysts in making better informed decisions. As a result, we expect our contributions to be a step towards the development of usable DP for IoT sensor data. |
URL | https://ieeexplore.ieee.org/document/9431047 |
DOI | 10.1109/PerComWorkshops51409.2021.9431047 |
Citation Key | kuhtreiber_usable_2021 |