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Hilbert curve-based cryptographic transformation scheme for spatial query processing on outsourced private data

机译:基于希尔伯特曲线的密码变换方案,用于外包私有数据的空间查询处理

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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. (C) 2015 Elsevier B.V. All rights reserved.
机译:随着云计算的发展,在外包数据库中保护位置数据隐私的研究已受到关注。但是,现有的空间变换方案容易受到各种攻击模型的攻击。现有的密码转换方案提供了良好的数据保密性,但是具有很高的查询处理成本。为了提高隐私性并降低成本,我们提出了一种基于希尔伯特曲线的密码转换方案,以保护空间数据的隐私性,以防止对外包数据库的各种攻击。我们还使用希尔伯特顺序索引提供有效的范围和k-NN查询处理算法。性能分析证实,与现有的密码转换方案相比,该方案对攻击模型具有鲁棒性,并具有更好的查询处理性能。 (C)2015 Elsevier B.V.保留所有权利。

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