Blockchain-based and Privacy-Preserving Data Collection for Vehicular Crowdsensing

In vehicular crowdsensing, vehicles frequently sense and transmit data, which poses a challenge in the privacy protection of vehicles. Existing privacy-preserving techniques often have a large computation or communication cost and the identity privacy protection is not well addressed. In this article, we propose a blockchain-based and privacy-preserving data collection scheme for vehicular crowdsensing, named BPDV. It aims to efficiently collect sensing data from vehicles while preserving the privacy of vehicles and requesters. BPDV assigns a sequence number to each vehicle that senses data by using a base-k 1-head random number, in order to protect the identity privacy. To save resources, the data from multiple vehicles are sent in one round of data collection with a well-designed "yield" mechanism. Additionally, RSUs store the sensing data on a blockchain to achieve decentralized and reliable data storage. Finally, extensive experiments show that BPDV has small computation and communication costs compared with other schemes, while providing the identity and data privacy preserving.