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ThinkMind // MOBILITY 2018, The Eighth International Conference on Mobile Services, Resources, and Users // View article mobility_2018_1_20_70017


Exploring Origin and Rotation Parameters While Using Hilbert Curves in Mobile Environments

Authors:
Anand Paturi
Subhasish Mazumdar

Keywords: Mobile Privacy; Spatial Transformation; Hilbert Curves; Location-Based Queries; Location-Based Service.

Abstract:
In mobile computing, nearest-neighbor queries are of the form “find me the nearest service of type S” or “find me k nearest services of type S.” It is known that such queries, while convenient for the consumer, are associated with privacy threats. For addressing such privacy threats, one of the approaches suggested by researchers is spatial transformation via Hilbert curves. A Hilbert curve fills a 2-dimensional grid with a one-dimensional sequence that may be viewed as a curve. It is thus usable as a hash function that is order-preserving, in the sense that adjacent elements in the single dimension represent physically contiguous space in two dimensions. It provides an encryption of the two-dimensional space coordinates with the parameters involved in its construction serving as the key. The origin of the two-dimensional grid that is conceptually overlaid on the physical space and the choice of two canonical forms of the curve are crucial elements of the key. In this paper, we examine the ramifications of these parameters on the Quality of Service (QoS) provided to mobile users and suggest that these parameters be chosen based on acceptable QoS thresholds. By considering rotation and transposition, we enhance the space of keys, thus providing more options in the choice of those parameters.

Pages: 8 to 13

Copyright: Copyright (c) IARIA, 2018

Publication date: July 22, 2018

Published in: conference

ISSN: 2308-3468

ISBN: 978-1-61208-656-9

Location: Barcelona, Spain

Dates: from July 22, 2018 to July 26, 2018

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