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EDBT
2016
ACM

Towards Privacy-preserving Mobile Location Analytics

3 years 20 days ago
Towards Privacy-preserving Mobile Location Analytics
Mobile Location Analytics (MLA) is enjoying increased attention. Typical businesses eager to exploit the opportunities offered by this emerging form of location-based services are venues of various types and size including retail stores, shopping malls, airports, hotels, and theme parks. MLA relies on applying statistical inference methods to sensory data constantly generated by mobile devices of (potential) customers/visitors or data collected by a variety of in-door sensors in order to generate useful insights into people’s behavior and interests. While providing venue operators and (potential) customers with many benefits, MLA also raises significant privacy concerns, given the sensitive nature of the data being collected and transferred to remote entities for further processing. In this paper, we offer a vision for building privacy and data protection into MLA. We argue for a holistic and user-centered approach, i.e., one enabling individuals whose data are collected and pro...
Marius Gassen, Hervais Simo Fhom
Added 02 Apr 2016
Updated 02 Apr 2016
Type Journal
Year 2016
Where EDBT
Authors Marius Gassen, Hervais Simo Fhom
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