1st ed. 2018 Edition
by Aris Gkoulalas-Divanis (Editor), Claudio Bettini (Editor)
This handbook covers the fundamental principles and theory, and the
state-of-the-art research, systems and applications, in the area of
mobility data privacy. It is primarily addressed to computer science and
statistics researchers and educators, who are interested in topics
related to mobility privacy. This handbook will also be valuable to
industry developers, as it explains the state-of-the-art algorithms for
offering privacy. By discussing a wide range of privacy techniques,
providing in-depth coverage of the most important ones, and highlighting
promising avenues for future research, this handbook also aims at
attracting computer science and statistics students to this interesting
field of research.
The advances in mobile devices and positioning
technologies, together with the progress in spatiotemporal database
research, have made possible the tracking of mobile devices (and their
human companions) at very high accuracy, while supporting the efficient
storage of mobility data in data warehouses, which this handbook
illustrates. This has provided the means to collect, store and process
mobility data of an unprecedented quantity, quality and timeliness. As
ubiquitous computing pervades our society, user mobility data represents
a very useful but also extremely sensitive source of information. On
one hand, the movement traces that are left behind by the mobile devices
of the users can be very useful in a wide spectrum of applications such
as urban planning, traffic engineering, and environmental pollution
management. On the other hand, the disclosure of mobility data to third
parties may severely jeopardize the privacy of the users whose movement
is recorded, leading to abuse scenarios such as user tailing and
profiling.
A significant amount of research work has been
conducted in the last 15 years in the area of mobility data privacy and
important research directions, such as privacy-preserving mobility data
management, privacy in location sensing technologies and location-based
services, privacy in vehicular communication networks, privacy in
location-based social networks, privacy in participatory sensing systems
which this handbook addresses.. This handbook also identifies
important privacy gaps in the use of mobility data and has resulted to
the adoption of international laws for location privacy protection
(e.g., in EU, US, Canada, Australia, New Zealand, Japan, Singapore), as
well as to a large number of interesting technologies for
privacy-protecting mobility data, some of which have been made available
through open-source systems and featured in real-world applications.
