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.
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