Paper Info
Title
Achieving Secure and Privacy-Preserving Incentive in Vehicular Cloud Advertisement Dissemination.
Abstract
The recent research trend of extending cloud computing to vehicles by leveraging under-utilized on-board capabilities [also known as vehicular cloud (VC)] is unsurprising, partly due to the increasing popularity of intelligent vehicles (with on-board computing equipment) and cloud computing. However, VC deployment is still challenging: how to securely verify responding vehicles, how to recruit competent vehicles, and how to achieve privacy preservation, are among the remaining research challenges. In this paper, we propose a secure and privacy-preserving incentive mechanism under the vehicular advertisement dissemination setting, which enables vehicles to opportunistically perform on-demand advertisement dissemination tasks and (financially) benefit from the completed task. Specifically, the road side unit (RSU) representing the advertisement dissemination server first announces a dissemination task, and performs the privacy-preserving access control of the responding vehicles. Then the RSU selects the participating vehicles among a pool of verified competent vehicles, and acknowledges the participation of selected vehicles with a secure secret sharing scheme; meanwhile, the selected vehicles performs the dissemination task with incentives. Finally, we prove the security of the proposed scheme in terms of secure access control and privacy preservation, and demonstrate its efficiency via simulation results (i.e., improves the amount of advertisement dissemination and brings incentives to participating vehicles).
Year
DOI
Venue
2018
10.1109/ACCESS.2018.2827365
IEEE ACCESS
Keywords
Field
DocType
Advertisement dissemination,incentive mechanism,privacy preservation,vehicular cloud
Software deployment,Secret sharing,Incentive,Advertising,Task analysis,Computer science,Popularity,Server,Computer network,Access control,Cloud computing
Journal
Volume
ISSN
Citations 
6
2169-3536
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Qinglei Kong1162.62
Rongxing Lu25091301.87
Hui Zhu38317.00
Maode Ma41255163.24