Journal
VEHICULAR COMMUNICATIONS
Volume 16, Issue -, Pages 62-71Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.vehcom.2019.03.001
Keywords
LBS; Fog computing; IoV; kNN query with type
Funding
- Academy of Finland [308087]
- NSFC [61672410, U1536202]
- Natural Science Basic Research Plan in Shaanxi Province of China [2016ZDJC-06]
- 111 project [B08038, B16037]
- National Postdoctoral Program for Innovative Talents [BX20180238]
- China Postdoctoral Science Foundation [2018M633461]
- National Natural Science Foundation of China (NSFC) [61802293]
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Public awareness on privacy stimulates many researches about privacy-preserving location based services (LBS) in terms of providing mutual privacy to both LBS and its users. However, the high latency of privacy preservation in LBS becomes a main obstacle for applying LBS to Internet of Vehicles (IoV). To solve this problem, we propose two privacy-preserving LBS query schemes (kNN and T-kNN) by taking the advance of fog computing and by applying oblivious transfer (OT) and ciphertext-policy attribute based encryption (CP-ABE). Given a query from a vehicle, both schemes return k nearest POIs as response, with the difference that T-kNN supports fine-grained type based POI queries. Based on our proposed oblivious key transfer and privacy-preserving secret key generation, both schemes preserve mutual privacy of both LBS provider and vehicles. Complexity analysis and empirical study show that our approach outperforms the other two state-of-the-art works. (C) 2019 Elsevier Inc. All rights reserved.
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