Towards Anonymizing Intermodal Mobility Data for Smart Cities.

As cities seek to optimize their resources for a sustainable and livable future, the concept of intermodal mobility has become increasingly important. However, the collection and analysis of intermodal mobility data is complicated by the need for robust anonymization methods, as privacy and security concerns remain paramount. Existing anonymization methods are either mode-specific or so complicated that they deter potential stakeholders. In this paper, we describe a variety of real mobility data sources for our upcoming field study. With that data, we plan to provide insights into infrastructure utilization and transitions between modes of transport. We further identified several anonymization techniques for mobility data to ensure privacy and acceptance among the citizens. To find suitable techniques for intermodal mobility data, we provide insights from our previous experience on anonymization and discuss the practicability of the identified techniques. Our paper highlights the need for explainable anonymization methods tailored to inter-modal mobility data that address privacy and security concerns and pave the way for more accessible privacy-compliant solutions.