Modern vehicles are equipped with a plethora of on-board sensors and large on-board\nstorage, which enables them to gather and store various local-relevant data. However, the wide\napplication of vehicular sensing has its own challenges, among which location-privacy preservation\nand data query accuracy are two critical problems. In this paper, we propose a novel range query\nscheme, which helps the data requester to accurately retrieve the sensed data from the distributive\non-board storage in vehicular ad hoc networks (VANETs) with location privacy preservation.\nThe proposed scheme exploits structured scalars to denote the locations of data requesters and\nvehicles, and achieves the privacy-preserving location matching with the homomorphic Paillier\ncryptosystem technique. Detailed security analysis shows that the proposed range query scheme can\nsuccessfully preserve the location privacy of the involved data requesters and vehicles, and protect\nthe confidentiality of the sensed data. In addition, performance evaluations are conducted to show\nthe efficiency of the proposed scheme, in terms of computation delay and communication overhead.\nSpecifically, the computation delay and communication overhead are not dependent on the length of\nthe scalar, and they are only proportional to the number of vehicles.
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