M.Sc. (Tech) Anna Brauer defends her PhD thesis "Preserving privacy and utility for urban microscale analyses in spatiotemporal trajectories" on Tuesday the 23rd of September 2025 at 13 o'clock in the University of Helsinki Main building, Auditorium Karolina Eskelin (U3032, Unioninkatu 34, 3rd floor). Her opponent is Professor Christian Kray (University of Münster, Germany) and custos Professor Laura Ruotsalainen (University of Helsinki). The defence will be held in English.
The thesis of Anna Brauer is a part of research done in the Department of Computer Science and in the Spatiotemporal Data Analysis group at the University of Helsinki. Her supervisors have been Professor Laura Ruotsalainen (University of Helsinki) and Professor Juha Oksanen (Finnish Geospatial Research Institute).
Preserving privacy and utility for urban microscale analyses in spatiotemporal trajectories
Spatiotemporal trajectories are digital traces of urban mobility that advance understanding of transport systems, human movement patterns, and their economic, environmental, and social implications. The steadily improving accuracy of positioning technologies and the ubiquity of embedded Global Navigation Satellite System (GNSS) sensors enable microscale trajectory analyses at the level of individual road sections or demographic groups. However, as mobility trajectories contain personal information, handling them raises privacy concerns. Existing research on privacy-preserving methods for trajectory data predominantly focuses on scenarios in which a trusted third party creates sanitized data products ranging from spatially distorted trajectories to aggregated or synthetic data. These methods are often not applicable to small or dynamically growing datasets and can significantly reduce the data's utility for microscale analyses.
This thesis addresses this gap by introducing privacy-preserving mechanisms for high-resolution mobility trajectories that retain spatiotemporal details and process individual trajectories directly on the client device. More precisely, the thesis contributes: (1) a suppression-based mechanism that implements a variant of k-anonymity to prevent the inference of sensitive locations based on the course of the trajectory; (2) mechanisms that obscure the time of recording using either a deterministic approach or a stochastic one inspired by metric differential privacy; and (3) a perturbation-based mechanism that mitigates attacks based on speed and its derivatives. The mechanisms are experimentally evaluated with utility measures and simulated re-identification attacks.
Applying these mechanisms in a practical setting, the thesis presents a pilot service for collecting trajectories of active movers for research purposes. The service enables cyclists and runners to contribute trajectories and sanitizes contributions according to a user-configurable privacy level. Building trust through transparency, this privacy-aware approach aims to help improve the availability of mobility trajectories for scientific research. The thesis demonstrates the value of this data through a study that uses cyclists' trajectories to estimate the smoothness of urban cycling across segments of the road network. Analyzing cyclists' motion and stopping behavior, the study proposes a measure to quantify urban bikeability that could support evidence-based infrastructure improvements. This underlines the potential of trajectory data and the need for privacy-preserving methods that balance privacy and utility for specific use cases.
Availability of the dissertation
An electronic version of the doctoral dissertation will be available in the University of Helsinki open repository Helda at http://urn.fi/URN:ISBN:978-952-84-1913-6.
Printed copies will be available on request from Anna Brauer: anna.brauer@helsinki.fi.