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In today's digital society, increasing amounts of contextually rich spatiotemporal information are collected and used, e.g., for knowledge-based decision making, research purposes, optimizing operational phases of city management, planning infrastructure networks, or developing timetables for public transportation with an increasingly autonomous vehicle fleet. At the same time, however, publishing or sharing spatio-temporal data, even in aggregated form, is not always viable owing to the danger of violating individuals' privacy, along with the related legal and ethical repercussions. In this chapter, we review some fundamental approaches for anonymizing and releasing spatio-temporal density, i.e., the number of individuals visiting a given set of locations as a function of time. These approaches follow different privacy models providing different privacy guarantees as well as accuracy of the released anonymized data. We demonstrate some sanitization (anonymization) techniques with provable privacy guarantees by releasing the spatio-temporal density of Paris, in France. We conclude that, in order to achieve meaningful accuracy, the sanitization process has to be carefully customized to the application and public characteristics of the spatio-temporal data.

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Over the last couple of years, industry operators' associations issued requirements towards an end-to-end management and orchestration plane for 5G networks. Consequently, standard organisations started their activities in this domain. This article provides an analysis and an architectural survey of these initiatives and of the main requirements, proposes descriptions for the key concepts of domain, resource and service slicing, end-to-end orchestration and a reference architecture for the end-to-end orchestration plane. Then, a set of currently available or under development domain orchestration frameworks are mapped to this reference architecture. These frameworks, meant to provide coordination and automated management of cloud and networking resources, network functions and services, fulfil multi-domain (i.e. multi-technology and multioperator) orchestration requirements, thus enabling the realisation of an end-to-end orchestration plane. Finally, based on the analysis of existing single-domain and multi-domain orchestration components and requirements, this paper presents a functional architecture for the end-to-end management and orchestration plane, paving the way to its full realisation.

Third-party applications on Facebook can collect personal data of the users who install them, but also of their friends. This raises serious privacy issues as these friends are not notified by the applications nor by Facebook and they have not given consent. This paper presents a detailed multi-faceted study on the collateral information collection of the applications on Facebook. To investigate the views of the users, we designed a questionnaire and collected the responses of 114 participants. The results show that participants are concerned about the collateral information collection and in particular about the lack of notification and of mechanisms to control the data collection. Based on real data, we compute the likelihood of collateral information collection affecting users: we show that the probability is significant and greater than 80% for popular applications such as TripAdvisor. We also demonstrate that a substantial amount of profile data can be collected by applications, which enables application providers to profile users. To investigate whether collateral information collection is an issue to users' privacy we analysed the legal framework in light of the new General Data Protection Regulation. We provide a detailed analysis of the entities involved and investigate which entity is accountable for the collateral information collection. To provide countermeasures, we propose a privacy dashboard extension that implements privacy scoring computations to enhance transparency towards collateral information collection. Furthermore, we discuss alternative solutions highlighting other countermeasures such as notification and access control mechanisms, cryptographic solutions and application auditing. To the best of our knowledge this is the first work that provides a detailed multi-faceted study of this problem and that analyses the threat of user profiling by application providers.