BcDKM: Blockchain-Based Dynamic Key Management Scheme for Crowd Sensing in Vehicular Sensor Networks

Vehicular sensor networks (VSNs) consist of vehicles equipped with various sensing devices, such as LiDAR. In a VSN, vehicles and/or roadside units (RSUs) can be organized into a vehicular cloud (VC) to enable the sharing of sensing and computational resources among participants, thereby supporting crowd-sensing applications. However, the highly dynamic nature of vehicular mobility poses significant challenges in terms of establishing secure and scalable group communication within the VC. To address these challenges, we first introduce a lightweight extension of the continuous group key agreement (CGKA) scheme by incorporating an administrator mechanism. The resulting scheme, referred to as CGKAwAM, supports the designation of multiple administrators within a single group for flexible member management. Building upon CGKAwAM, we propose a blockchain-based dynamic key management scheme, termed BcDKM. This scheme supports asynchronous join and leave operations while achieving communication round optimality. Furthermore, RSUs are leveraged as blockchain nodes to enable decentralized VC discovery and management, ensuring scalability without relying on a centralized server. We formally analyze the security of both CGKAwAM and BcDKM. The results demonstrate that the proposed scheme satisfies several critical security properties, including known-key security, forward secrecy, post-compromise security, and vehicle privacy. Experimental evaluations further confirm that BcDKM is practical and achieves a well-balanced tradeoff between security and performance.

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Publication Details

Journal
Sensors
Published
2025-09-12
DOI
https://doi.org/10.3390/s25185699
Primary Topic
Security in Wireless Sensor Networks
Type
article
Field-Weighted Citation Impact
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article

BcDKM: Blockchain-Based Dynamic Key Management Scheme for Crowd Sensing in Vehicular Sensor Networks

Ru Meng, Lei Zhang, Mingrui Zhang
Sensors
Security in Wireless Sensor Networks
article

BcDKM: Blockchain-Based Dynamic Key Management Scheme for Crowd Sensing in Vehicular Sensor Networks

Ru Meng, Lei Zhang, Mingrui Zhang
article en

Abstract

Vehicular sensor networks (VSNs) consist of vehicles equipped with various sensing devices, such as LiDAR. In a VSN, vehicles and/or roadside units (RSUs) can be organized into a vehicular cloud (VC) to enable the sharing of sensing and computational resources among participants, thereby supporting crowd-sensing applications. However, the highly dynamic nature of vehicular mobility poses significant challenges in terms of establishing secure and scalable group communication within the VC. To address these challenges, we first introduce a lightweight extension of the continuous group key agreement (CGKA) scheme by incorporating an administrator mechanism. The resulting scheme, referred to as CGKAwAM, supports the designation of multiple administrators within a single group for flexible member management. Building upon CGKAwAM, we propose a blockchain-based dynamic key management scheme, termed BcDKM. This scheme supports asynchronous join and leave operations while achieving communication round optimality. Furthermore, RSUs are leveraged as blockchain nodes to enable decentralized VC discovery and management, ensuring scalability without relying on a centralized server. We formally analyze the security of both CGKAwAM and BcDKM. The results demonstrate that the proposed scheme satisfies several critical security properties, including known-key security, forward secrecy, post-compromise security, and vehicle privacy. Experimental evaluations further confirm that BcDKM is practical and achieves a well-balanced tradeoff between security and performance.

SensorsVol. 25(18)
Jinan University (CN), Shanghai Key Laboratory of Trustworthy Computing (CN), East China Normal University (CN)
Openalex Percentile: Top 71%
Security in Wireless Sensor Networks
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BcDKM: Blockchain-Based Dynamic Key Management Scheme for Crowd Sensing in Vehicular Sensor Networks — Ru Meng, Lei Zhang, et al. · Sensors (2025) | TGRS Research Map | TGRS