Bidirectional Authentication for Safe Ridesharing Empowered by Permissioned Blockchain

Ridesharing and on-demand mobility systems offer societal benefits that include reduced traffic, lower parking demand and less environmental impact from vehicle usage. However, the problem of user impersonation has compromised the safety of both riders and drivers, sometimes ending in fatal tragedy. To address the safety concerns resulting from user impersonation, this paper proposes a blockchain-based and zero-knowledge approach for decentralized and privacy-preserving identity verification in ridesharing. The proposed permissioned blockchain facilitates our privacy-aware verification scheme and provides fine-grained access control policies to protect on-chain trip records. We developed the proposed system on the Hyperledger Fabric platform, with Chaincode smart contracts and Hyperledger Ursa cryptographic library. To measure the performance of the system, we conduct extensive experiments utilizing the Hyperledger Caliper benchmark tool. Our results show that the zero-knowledge proof module can perform the privacy-preserving identity verification at the millisecond level while the blockchain network offers low latency and high throughput for transactions. The non-resource-intensive authentication scheme and the proposed secure-by-design blockchain with access control policies make the proposed approach fitting for application in real-world ridesharing environments.

Authors

Institutions

Publication Details

Published
2025-06-20
DOI
https://doi.org/10.1109/gbc60041.2025.11134467
Citations
1
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
3.25
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bidirectional Authentication for Safe Ridesharing Empowered by Permissioned Blockchain

Mark Nejad, Hao Guo, Jie Zhang, Collin Meese et al.
1 citations
Blockchain Technology Applications and Security
3.25
article

Bidirectional Authentication for Safe Ridesharing Empowered by Permissioned Blockchain

Mark Nejad, Hao Guo, Jie Zhang, Collin Meese, Wanxin Li
article en
1 citations

Abstract

Ridesharing and on-demand mobility systems offer societal benefits that include reduced traffic, lower parking demand and less environmental impact from vehicle usage. However, the problem of user impersonation has compromised the safety of both riders and drivers, sometimes ending in fatal tragedy. To address the safety concerns resulting from user impersonation, this paper proposes a blockchain-based and zero-knowledge approach for decentralized and privacy-preserving identity verification in ridesharing. The proposed permissioned blockchain facilitates our privacy-aware verification scheme and provides fine-grained access control policies to protect on-chain trip records. We developed the proposed system on the Hyperledger Fabric platform, with Chaincode smart contracts and Hyperledger Ursa cryptographic library. To measure the performance of the system, we conduct extensive experiments utilizing the Hyperledger Caliper benchmark tool. Our results show that the zero-knowledge proof module can perform the privacy-preserving identity verification at the millisecond level while the blockchain network offers low latency and high throughput for transactions. The non-resource-intensive authentication scheme and the proposed secure-by-design blockchain with access control policies make the proposed approach fitting for application in real-world ridesharing environments.

Northwestern Polytechnical University (CN), Xi’an Jiaotong-Liverpool University (CN), University of Delaware (US)
Openalex Percentile: Top 7%
Blockchain Technology Applications and Security
3.25
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.