Privacy-preserving Blockchain-assisted private-parking scheme with efficient matching

Abstract

Due to the drastic increase in the number of vehicles, searching for available parking spots has become a major problem for drivers, especially in crowded and big cities. Thus, a smart parking system is crucial not only to facilitate drivers’ ability to find parking spaces, but also to reduce traffic congestion, pollution, and vehicles’ gas consumption. A growing number of public parking lots have been constructed to provide parking spots for drivers. Meanwhile, homeowners and landowners leave their private spaces that can be utilized and rented for other drivers seeking parking spaces. This paper proposes a decentralized smart private-parking scheme built on top of Blockchain. Blockchain is used to run and organize the developed parking scheme to help drivers find nearby parking spots owned by private homeowners and landowners. However, parking owners and drivers should send requests/offers that include the location/time information of spots and/or desired locations to park at. This information can be used to track daily live activities for both drivers and parking owners such as whether a parking owner is at home or not, drivers’ destinations, etc. To preserve privacy, in the proposed scheme, drivers/parking owners submit their requests/offers in an encrypted format, and the Blockchain can find feasible matches among the encrypted requests and offers without the need to get access to original sensitive information. In addition, an overlapping and partitioning technique is used to generate the requests/offers to increase matching results by finding more nearby drivers to park and thus maximizing parking owners’ profits. Finally, the proposed scheme has been implemented on Hyperledger Blockchain and extensive evaluations have been conducted using different simulation scenarios. The results indicate that the scheme is efficient in terms of scalability and throughput under different case scenarios. Also, security and privacy analysis are conducted to demonstrate that the scheme can run the services securely while ensuring drivers/parking owners’ privacy.