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Open AccessArticle

Secure Nearest Neighbor Query on Crowd-Sensing Data

1
School of Computer Science and Technology, Anhui University, Hefei 230601, China
2
School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China
*
Author to whom correspondence should be addressed.
Academic Editor: Yike Guo
Sensors 2016, 16(10), 1545; https://doi.org/10.3390/s16101545
Received: 19 July 2016 / Revised: 5 September 2016 / Accepted: 14 September 2016 / Published: 22 September 2016
(This article belongs to the Special Issue Big Data and Cloud Computing for Sensor Networks)
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. View Full-Text
Keywords: secure nearest neighbor; crowd-sensing; privacy-preservation; secure two-party computation; collusion attack secure nearest neighbor; crowd-sensing; privacy-preservation; secure two-party computation; collusion attack
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MDPI and ACS Style

Cheng, K.; Wang, L.; Zhong, H. Secure Nearest Neighbor Query on Crowd-Sensing Data. Sensors 2016, 16, 1545.

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