Citation

Jiang, Zheng (2025) Privacy protection framework for safety Beacon Message Management in the Internet of Vehicles. PhD thesis, Multimedia University.

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Abstract

The rapid evolution of the Internet of Vehicles (IoV) has transformed intelligent transportation systems, yet it exposes users to severe privacy risks concerning identity disclosure and location trajectory tracking through Safety Beacon Messages (SBMs). Current solutions face critical limitations: centralized architectures create vulnerable single points of failure, whilst blockchain-based approaches fail to balance high throughput demands with stringent privacy requirements. This research develops a comprehensive Privacy Protection Framework (PPF) that systematically protects SBM data across its lifecycle. The PPF integrates three core components: First, the SBM Separation Algorithm (SBM-SA) decouples vehicle identity from location information through dynamic group-based anonymization, defending against spatiotemporal inference attacks whilst maintaining data utility. Second, the PrivacyPreserving Data Uploading Scheme (PriDUS) secures vehicle-to-edge transmission by combining Threshold Secret Sharing Algorithm (TSSA) with dynamic vehicular grouping, transforming persistent identifiers into ephemeral sub-identifiers to prevent identity linkage. Third, the Master-Slave Multi-Chain (MSMC) blockchain architecture with Adaptive Grouping PBFT (AG-PBFT) consensus employs localized slave chains for high-frequency transactions and a central master chain for coordination, with AG-PBFT dynamically selecting nodes based on reputation to optimize scalability. Evaluation through simulations using realistic vehicular datasets (HighD) and OPNET-Fabric co-simulation demonstrates that AG-PBFT reduces consensus latency by 35% and increases transaction throughput by 28% compared to standard PBFT, whilst privacy modules achieve over 96% success in preventing identity linkage attacks. This research contributes a scalable, high-performance solution that effectively balances data privacy with operational efficiency for IoV environments.

Item Type:	Thesis (PhD)
Additional Information:	Call No.: TE228.37 .J53 2025
Uncontrolled Keywords:	Vehicular ad hoc networks (Computer networks)
Subjects:	T Technology > TE Highway engineering. Roads and pavements > TE210-228.3 Construction details Including foundations, maintenance, equipment
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	06 Mar 2026 01:34
Last Modified:	06 Mar 2026 01:51
URII:	http://shdl.mmu.edu.my/id/eprint/15453

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