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Privacy of Spatial Trajectories

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Computing with Spatial Trajectories

Abstract

The ubiquity of mobile devices with global positioning functionality (e.g., GPS and Assisted GPS) and Internet connectivity (e.g., 3G and Wi-Fi) has resulted in widespread development of location-based services (LBS). Typical examples of LBS include local business search, e-marketing, social networking, and automotive traffic monitoring. Although LBS provide valuable services for mobile users, revealing their private locations to potentially untrusted LBS service providers pose privacy concerns. In general, there are two types of LBS, namely, snapshot and continuous LBS. For snapshot LBS, a mobile user only needs to report its current location to a service provider once to get its desired information. On the other hand, a mobile user has to report its location to a service provider in a periodic or on-demand manner to obtain its desired continuous LBS. Protecting user location privacy for continuous LBS is more challenging than snapshot LBS because adversaries may use the spatial and temporal correlations in the user's a sequence of location samples to infer the user's location information with a higher degree of certainty. Such user spatial trajectories are also very important for many applications, e.g., business analysis, city planning, and intelligent transportation. However, publishing original spatial trajectories to the public or a third party for data analysis could pose serious privacy concerns. Privacy protection in continuous LBS and trajectory data publication has increasingly drawn attention from the research community and industry. In this chapter, we describe the state-of-the-art privacy-preserving techniques for continuous LBS and trajectory publication.

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Author information

Authors and Affiliations

  1. City University of Hong Kong, Hong Kong, China

    Chi-Yin Chow

  2. University of Minnesota, Twin Cities, USA

    Mohemad F. Mokbel

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  1. Chi-Yin Chow
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  2. Mohemad F. Mokbel
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Editors and Affiliations

  1. Microsoft Research Asia, Beijing, 100080, China, People's Republic

    Yu Zheng

  2. , School of Information Technology, University of Queensland, Brisbane, 4072, Queensland, Australia

    Xiaofang Zhou

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Chow, CY., Mokbel, M.F. (2011). Privacy of Spatial Trajectories. In: Zheng, Y., Zhou, X. (eds) Computing with Spatial Trajectories. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1629-6_4

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  • DOI: https://doi.org/10.1007/978-1-4614-1629-6_4

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