Towards Efficient and Auditable Heterogeneous Data Management in Vehicular Edge Networks

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Puhe Hao, Rui Han, Yu Wang, Mingfa Wan, Teng Yuan, Guozi Sun

Published: 2025, Last Modified: 08 Jan 2026CSCWD 2025EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: With the continuous and rapid development of the Internet of Vehicles, vehicular data is experiencing explosive growth. Vehicular edge computing and blockchain have been proposed to face this challenge, but today's data service providers find it challenging to adequately meet the demands of efficiency and security in time-sensitive scenarios with huge data volumes and heterogeneous data types. In this paper, we propose an efficient vehicular data management scheme to expand storage capacity and operational efficiency. Specifically, we coupled blockchain and the Interplanetary File System (IPFS) to tackle the heterogeneous data type issue. Attribute-based searchable encryption is exploited to facilitate the data management process. Real-time data tracker is proposed to enforce personalized driver behavior auditing and data tracking. We implement a prototype system based on FIBOS1blockchain platform. Experiments conducted show the storage efficiency of the system with a 98.76% storage reduction ratio and the high speed with a performance of approximately 1300 TPS (Transactions per second). The security analysis shows the promise of ensuring data confidentiality, integrity, and security.