Analysis of mobile network data for the study of mobility, respectful of privacy : Application to the road freight transport sector ; Analyse de données de signalisation mobile pour l’étude de la mobilité respectueuse de la vie privée : Application au secteur du transport routier de marchandises

Mobile network operators have a significant data source derived from communications of all connected objects (not just smartphones) with the network. These signaling data is a massive source of location data and are regularly used for the mobility analysis. However, potential uses face two major challenges: their low spatiotemporal precision and their highly sensitive nature concerning privacy.In the first phase, the thesis work enhances the understanding of the mobility state (stationary or in motion), speed, direction of movement of connected objects, and the route they take on a transportation infrastructure (e.g., road or rail).In the second phase, we demonstrate how to ensure the confidentiality of continuously produced mobility statistics. The use of signaling data, whether related to users or various connected objects, is legally regulated. For the study of mobility, operators tend to publish anonymized statistics (aggregated data). Specifically, the aim is to calculate complex and anonymized mobility statistics "on the fly" using differential privacy methods and probabilistic data structures (such as Bloom filters).Finally, in the third phase, we illustrate the potential of signaling data and the proposed approaches in this manuscript for quasi-real-time calculation of anonymous statistics on road freight transport. However, this is just an example of what could apply to other subjects analyzing population behaviors and activities with significant public and economic policy implications. ; Les opérateurs de réseau mobile disposent d'une importante source de données issue des communications de l'ensemble des objets connectés (smartphones mais pas uniquement) avec le réseau. Ces données de signalisation constituent une source massive de données de localisation et sont régulièrement utilisées pour l'étude de la mobilité (humaine ou non). Cependant, les usages potentiels se heurtent à deux écueils majeurs: leur faible précision spatiotemporelle et leur caractère éminemment sensible au regard de la protection ...