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Erratum published on 19 July 2019, see Sensors 2019, 19(14), 3187.
Open AccessArticle

A Privacy Preserving Scheme for Nearest Neighbor Query

1
Research Center of Computer Network and Information Security Technology, Harbin Institute of Technology, Harbin 150001, China
2
Cyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou 510006, China
3
School of Information Technology, Carleton University, Ottawa, ON K1S 5B6, Canada
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(8), 2440; https://doi.org/10.3390/s18082440
Received: 3 June 2018 / Revised: 23 July 2018 / Accepted: 25 July 2018 / Published: 27 July 2018
In recent years, location privacy concerns that arise when using the nearest neighbor query services have gained increasing attention, as such services have become pervasive in mobile social networks devices and the IoT environments. State-of-the-art privacy preservation schemes focus on the obfuscation of the location information, which has suffered from various privacy attacks and the tradeoff of the quality of service. By noticing the fact that the user’s location could be replaced by their surrounding wireless sensor infrastructures in proximity, in this paper, we propose a wireless sensor access point-based scheme for the nearest neighbor query, without using the location of the user. Then, a noise-addition-based method that preserves user’s location privacy was proposed. To further strengthen the adaptability of the approach to real-world environments, several performance-enhancing methods are introduced, including an R-tree-based Noise-Data Retrieval Algorithm (RNR), and a nearest neighbor query method based on our research. Both performance and security evaluations are conducted to validate our approach. The results show the effectiveness and the practicality of our work. View Full-Text
Keywords: location privacy; nearest neighbor query; noise addition; R-tree; wireless sensor localization; Internet of Things location privacy; nearest neighbor query; noise addition; R-tree; wireless sensor localization; Internet of Things
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Wang, Y.; Tian, Z.; Zhang, H.; Su, S.; Shi, W. A Privacy Preserving Scheme for Nearest Neighbor Query. Sensors 2018, 18, 2440.

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