Article ID Journal Published Year Pages File Type
378690 Data & Knowledge Engineering 2016 13 Pages PDF
Abstract

Research on preserving location data privacy in outsourced databases has been spotlighted with the development of cloud computing. However, the existing spatial transformation schemes are vulnerable to various attack models. The existing cryptographic transformation scheme provides good data privacy, but it has a high query processing cost. To improve privacy and reduce cost, we propose a Hilbert curve-based cryptographic transformation scheme to preserve the privacy of the spatial data from various attacks on outsourced databases. We also provide efficient range and k-NN query processing algorithms using a Hilbert-order index. A performance analysis confirms that the proposed scheme is robust against attack models and achieves better query processing performance than the existing cryptographic transformation scheme.

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Physical Sciences and Engineering Computer Science Artificial Intelligence
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