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Exploring Spatial Transformation-Based Privacy in a Small Town

Authors:
Aidan Jacobs
Subhasish Mazumdar

Keywords: Mobile environments; Location-dependent and sensitive; Privacy; Query Processing.

Abstract:
As mobile devices become increasingly prevalent in society, the expected utility of such devices rises; arguably, the most impact comes from location-based services as they provide tremendous benefits to mobile users. These users also value privacy, i.e., keeping their locations and search queries private, but that is not easy to achieve. It has been previously proposed that user location privacy can be secured through the use of space filling curves due to their ability to preserve spatial proximity while hiding the actual physical locations. With a space filling curve, such as the Hilbert curve, an application that provides location-based services can allow the user to take advantage of those services without transmitting a physical location. Earlier research has uncovered vulnerabilities of such systems and proposed remedies. But those countermeasures were clearly aimed at reasonably large metropolitan areas. It was not clear if they were appropriate for small towns, which display sparsity of Points of Interest (POIs) and limited diversity in their categories. This paper studies the issue focusing on a small university town.

Pages: 8 to 13

Copyright: Copyright (c) IARIA, 2023

Publication date: June 26, 2023

Published in: conference

ISSN: 2308-3468

ISBN: 978-1-68558-074-2

Location: Nice, France

Dates: from June 26, 2023 to June 30, 2023