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Abstract
Mobile network operators collect information about the movements of their subscribers via passive or active monitoring of mobile device locations. The recorded trajectories offer an unprecedented outlook on the activities of large user populations, which enables developing new networking solutions and services, and scaling up studies in multiple research disciplines. Yet, the disclosure of individual trajectories raises significant privacy concerns that personal data protection regulations are translating into legal requirements. Meeting such requirements creates a need for solutions that anonymise mobile phone trajectories while preserving data quality. In this talk, I will present contributions to the design of such solutions. Specifically, I will discuss the optimal merging of trajectories, which is a key operation for the generalisation of this type of data; I will then show how to leverage the results to implement two important privacy principles, indistinguishability and uninformativeness, in mobile phone trajectory data.
Speaker bio
Marco Fiore is a permanent researcher at CNR-IEIIT, Italy, a visiting research fellow at University College London (UCL), UK, and a EU Marie Curie fellow. Marco received MSc degrees from the University of Illinois at Chicago, IL, USA, and Politecnico of Torino, Italy, a PhD degree from Politecnico di Torino, Italy, and a Habilitation à Diriger des Recherches (HDR) from Université de Lyon, France. He was Maître de Conférences (Associate Professor) at Institut National des Sciences Appliquées (INSA) de Lyon, France, Associate Researcher at Inria, France, visiting research fellow at Rice University, TX, USA, and Universitat Politècnica de Catalunya (UPC), Spain. Marco is a recipient of the French national Scientific Excellence Award (PES), EU Marie Curie Career Reintegration Grant, Royal Society International Exchange Fellowship, Data Transparency Lab grant, and a Finalist at the Telecom Italia Big Data Challenge. He is a senior member of IEEE, and a member of ACM.