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Sensors 2017, 17(7), 1611; https://doi.org/10.3390/s17071611

A Fine-Grained and Privacy-Preserving Query Scheme for Fog Computing-Enhanced Location-Based Service

The Information Security and National Computing Grid Laboratory, Southwest Jiaotong University, Chengdu 610031, China
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Received: 31 May 2017 / Revised: 29 June 2017 / Accepted: 7 July 2017 / Published: 11 July 2017
(This article belongs to the Special Issue Security and Privacy Challenges in Emerging Fog Computing)
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Abstract

Location-based services (LBS), as one of the most popular location-awareness applications, has been further developed to achieve low-latency with the assistance of fog computing. However, privacy issues remain a research challenge in the context of fog computing. Therefore, in this paper, we present a fine-grained and privacy-preserving query scheme for fog computing-enhanced location-based services, hereafter referred to as FGPQ. In particular, mobile users can obtain the fine-grained searching result satisfying not only the given spatial range but also the searching content. Detailed privacy analysis shows that our proposed scheme indeed achieves the privacy preservation for the LBS provider and mobile users. In addition, extensive performance analyses and experiments demonstrate that the FGPQ scheme can significantly reduce computational and communication overheads and ensure the low-latency, which outperforms existing state-of-the art schemes. Hence, our proposed scheme is more suitable for real-time LBS searching. View Full-Text
Keywords: location-based services (LBS); fog computing; low-latency; fine-grained; privacy-preserving location-based services (LBS); fog computing; low-latency; fine-grained; privacy-preserving
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Yang, X.; Yin, F.; Tang, X. A Fine-Grained and Privacy-Preserving Query Scheme for Fog Computing-Enhanced Location-Based Service. Sensors 2017, 17, 1611.

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