Privacy-Preserving Traffic Management: A Blockchain and Zero-Knowledge Proof Inspired Approach

Wanxin Li, Hao Guo, Mark Nejad, Chien-Chung Shen

Research output: Contribution to journalArticlepeer-review

74 Citations (Scopus)

Abstract

Incorporation of connected vehicle (CV) data into real-time traffic management systems presents a host of new challenges resulting from the current lack of data integrity and data privacy in traffic networks. Over the past few years, blockchain technologies have been inspiring extensive innovations in the transportation field. However, due to the transparency property, sensitive data stored on the blockchain would be accessible to anyone, resulting in a lack of privacy. In this paper, we propose a decentralized and location-aware architecture to address the data integrity along with the privacy-preserving issues in blockchain-based traffic management systems. Our proposed architecture integrates with permissioned and modular blockchain network and non-interactive zero-knowledge range proof (ZKRP) protocol. We develop the prototype system on the Hyperledger Fabric platform and Hyperledger Ursa cryptographic library. The performance results show that our approach is effective and feasible for real-time traffic management while preserving the data privacy requirements.
Original languageEnglish
Pages (from-to)181733-181743
JournalIEEE Access
Volume8
DOIs
Publication statusPublished - 2020

Keywords

  • Logic gates
  • Data privacy
  • Fabrics
  • Protocols
  • Cryptography
  • Computer architecture
  • Blockchain
  • connected vehicle
  • data integrity
  • data privacy
  • traffic management
  • vehicular network
  • zero-knowledge range proof

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