A blog to accompany the work on my dissertation on human mobility data and privacy.
This week I registered my Ph.D. proposal with the working title “Privacy-preserving Analytics of Human Mobility Data – Minimizing the utility-privacy trade-off for urban mobility applications in practice” at the Technische Universität Berlin (TU Berlin). This is what I am going to work on:
In recent years, data on human mobility has become increasingly available. Thanks to GPS, cellular networks, and smartphones, people's whereabouts are continuously recorded and stored. This provides an unprecedented resource for useful applications such as urban planning. At the same time, as more and more data becomes available, the privacy of individuals is increasingly at risk. As a result, there is already a growing body of research looking at privacy-preserving measures of mobility data. Such measures, however, come with a utility-privacy trade-off, where the usefulness of the data is traded for privacy. State-of-the-art techniques such as measures with differential privacy guarantees are not (yet) applied to a large extend in practical settings. Lack of knowledge, complicated procedures, and fear of potentially inaccurate analysis results are potential reasons that prevent their implementation. This thesis aims to close the gap between theory and practice. Privacy-preserving measures for human mobility data will be researched, suitable measures for practical use cases will be identified, implemented, and evaluated to contribute to a solid foundation of research for human mobility analytics in real-world applications.
With this blog, I want to accompany my work with a special focus on real-life use cases and implementations in Python and R. I thereby hope to make the academic research more accessible to anybody working with human mobility data who has (or should have) the want or need to make their analyses more privacy-preserving. I also hope to spark some interest for the topic of privacy which is often rather perceived as an annoying necessity.
Additionally, I would very much appreciate an exchange with other researchers and practitioners who work in this field. Therefore, any feedback, further insights, opposing opinions, or just an informal chat on this topic are always welcome: email@example.com