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Secure Nearest Neighbor Query on Crowd-Sensing Data

机译:对人群感应数据的安全最近邻居查询

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摘要

Nearest neighbor queries are fundamental in location-based services, and secure nearest neighbor queries mainly focus on how to securely and quickly retrieve the nearest neighbor in the outsourced cloud server. However, the previous big data system structure has changed because of the crowd-sensing data. On the one hand, sensing data terminals as the data owner are numerous and mistrustful, while, on the other hand, in most cases, the terminals find it difficult to finish many safety operation due to computation and storage capability constraints. In light of they Multi Owners and Multi Users (MOMU) situation in the crowd-sensing data cloud environment, this paper presents a secure nearest neighbor query scheme based on the proxy server architecture, which is constructed by protocols of secure two-party computation and secure Voronoi diagram algorithm. It not only preserves the data confidentiality and query privacy but also effectively resists the collusion between the cloud server and the data owners or users. Finally, extensive theoretical and experimental evaluations are presented to show that our proposed scheme achieves a superior balance between the security and query performance compared to other schemes.
机译:最近邻居查询是基于位置的服务的基础,安全的最近邻居查询主要集中在如何安全,快速地检索外包云服务器中的最近邻居。但是,由于拥挤的数据,以前的大数据系统结构发生了变化。一方面,感测作为数据所有者的数据终端是众多且不信任的,另一方面,在大多数情况下,由于计算和存储能力的限制,终端难以完成许多安全操作。针对人群感知数据云环境中的多所有者和多用户(MOMU)情况,本文提出了一种基于代理服务器架构的安全最近邻居查询方案,该方案由安全的两方计算协议和安全的Voronoi图算法。它不仅保留了数据机密性和查询隐私性,而且还有效地抵抗了云服务器与数据所有者或用户之间的串通。最后,广泛的理论和实验评估表明,与其他方案相比,我们提出的方案在安全性和查询性能之间实现了出色的平衡。

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