Room 1.1/2 IMDEA Networks Institute, Avda. del Mar Mediterráneo 22, 28918 Leganés – Madrid
Collecting data generated by widespread digital transactions is an increasingly common practice. The likes of telecommunication network operators, mobile service providers, app developers and financial companies have the possibility to track the movements, preferences, activities and habits of large populations of individuals. Mining of such high-dimensional big data paves the way to new, compelling models across economic and scientific domains that could not be foreseen until a few years ago, and are in some cases becoming part of our everyday life. The other side of the coin is the emergence of novel privacy issues related to the collection, storage and exploitation of such sensible information. While regulations are currently being drafted to provide a legal framework to activities on digital transaction data, these need to be backed up by sound technical solutions that transform the raw data so as to ensure that users' privacy is preserved at all phases of data processing. In this work, we first unveil the reasons for the poor anonymizability of mobile traffic datasets, by leveraging an original measure of the anonymizability of users’ mobile trajectories. Building on such findings, we propose different algorithms that enforce original privacy criteria on trajectories through specialized generalization.
About Marco Gramaglia
Marco Gramaglia is a post-doc researcher at University Carlos III of Madrid (UC3M). He received an M.Sc (2009) and a Ph.D (2012) in Telematics Engineering from the same university and a M.Sc. degree (2009) in Computer Science engineering from Politecnico di Torino.
Before joining UC3M, he held post-doctoral research positions at Istituto Superiore Mario Boella (Torino, Italy), the Institute of Electronics, Computer, and Telecommunications Engineering (IEIIT) of the National Research Council of Italy (CNR, Torino, Italy) and at the IMDEA Networks institute (Madrid, Spain).
He likes researching on several aspects of mobile networks, ranging from vehicular networking to future 5G Networks. He is also interested in Big Data analytics and end user privacy.
This event will be conducted in English