An efficient privacy-preserving data query and dissemination scheme in vehicular cloud

Vehicular Cloud (VC) improves the utilization of idle resources in vehicles by providing data services for other vehicles or entities such as data computing and storage. However, the vehicles in the VC still face privacy and security issues, especially when querying data from the road side unit. To this end, in this paper, we propose an efficient privacy-preserving data query and dissemination scheme, named EPDQD, for VC. More precisely, by using the lightweight homomorphic encryption technique and the Chinese Remainder Theorem, the road side unit can aggregate and recover multiple data query requests without knowing the linkability of the data query request and its origin vehicle. EPDQD also adopts the message authentication code and non-interactive secure session keys to achieve the authentication of data query requests and the integrity of data transmission. Detailed security analysis indicates that EPDQD can resist various security threats. In addition, the performance evaluations demonstrate that EPDQD can significantly reduce computation complexity and communication overhead. (c) 2020 Elsevier B.V. All rights reserved.