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Transdisciplinary exploration of the privacy-aware usage of movement data for sustainable urban mobility research (FreeMove)

Lupe

FreeMove is a transdisciplinary project funded by the Federal Ministry of Education and Research (BMBF) to explore mobility data. The consortium combines expertise from the fields of machine learning, digital self-determination, human-centered computing and information security. The scientific perspective is provided by departments of the HTW Berlin, FU Berlin, TU Berlin, and UdK Berlin. The German Aerospace Center (DLR) and the Technologiestiftung Berlin extend this scientific perspective with a focus on implementation issues and stakeholder engagement.

The potential of the analysis of movement data is enormous. For example for coping with critical problems such as epidemics and catastrophes as well as for sustainable, human-centered and environmentally conscious urban and transport planning. In contrast, there are a number of challenges associated with making such data available: the legally and ethically required high level of protection of the privacy of individuals. This calls for sophisticated technical and mathematical anonymisation procedures. However, there is always a trade-off between the usability of the data, for example for statistical and algorithmic modelling procedures, on the one hand, and data protection and data security on the other. Therefore, there is a need to ​establish a publicly acceptable balance between access to information and the protection of privacy.

In the project, we develop a holistic theoretical and conceptual framework, which systematically maps the versatile requirements for a fair, useful, secure and understandable provision of movement data and harmonises the different values of the stakeholders. On the basis of three concrete representative use cases from the field of urban mobility, we will explicitly develop and bring together suitable methods and implement them prototypically. Based on this, the project will develop recommendations for action for the various stakeholders

In the FreeMove project, our department analyses, assesses, and evaluates anonymisation methods with regard to privacy guarantees. Moreover, we are interested in the generation of synthetic mobility data and its technical privacy guarantees.

Cooperation partners

  • Freie Universität Berlin
  • Deutsches Zentrum für Luft- und Raumfahrt
  • Hochschule für Technik und Wirtschaft Berlin
  • Universität der Künste Berlin
  • Technologiestiftung Berlin

Publications

Luise Mehner and Saskia Nuñez von Voigt and Florian Tschorsch (2021). Towards Explaining Epsilon: A Worst-Case Study of Differential Privacy Risks. 2021 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), 328-331.

Link to publication Link to original publication

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