Blockchain driven trust management for intelligent transportation systems in VANETs

Vehicular Ad Hoc Networks (VANETs) are a key component of Intelligent Transportation Systems (ITS), enabling vehicle-to-everything (V2X) communication to improve traffic efficiency and road safety. However, maintaining strong network performance and user privacy requires robust security mechanisms. Unlike existing blockchain-VANET solutions that address isolated aspects, our framework uniquely integrates Physical Unclonable Functions (PUFs) for lightweight authentication, an Enhanced Quantified role-based Practical Byzantine Fault Tolerance (EQPBFT) consensus mechanism for efficient and secure block creation, and a Deep Neural Network (DNN)-based intrusion detection system into a unified trust management pipeline. The EQPBFT algorithm improves network resilience by efficiently identifying and mitigating malicious nodes during block creation. In addition, a DNN-based intrusion detection system enhances threat classification and strengthens attack detection accuracy. Simulation results demonstrate reduced computation time (up to 25% lower than PBFT), faster block creation (5.2 ms vs. 6.6 ms for 200 nodes), and higher intrusion detection accuracy (95%) compared to baseline models. These quantitative outcomes validate the robustness and efficiency of the proposed system.

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Publication Details

Journal
Scientific Reports
Published
2025-11-12
DOI
https://doi.org/10.1038/s41598-025-23351-x
Citations
1
Primary Topic
Vehicular Ad Hoc Networks (VANETs)
Type
article
Field-Weighted Citation Impact
0.73

Funders

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article

Blockchain driven trust management for intelligent transportation systems in VANETs

P. Vetrivelan, Elizabeth Chang, V Hariharasudhan
1 citations
Scientific Reports
Vehicular Ad Hoc Networks (VANETs)
0.73
article

Blockchain driven trust management for intelligent transportation systems in VANETs

P. Vetrivelan, Elizabeth Chang, V Hariharasudhan
article en
1 citations

Abstract

Vehicular Ad Hoc Networks (VANETs) are a key component of Intelligent Transportation Systems (ITS), enabling vehicle-to-everything (V2X) communication to improve traffic efficiency and road safety. However, maintaining strong network performance and user privacy requires robust security mechanisms. Unlike existing blockchain-VANET solutions that address isolated aspects, our framework uniquely integrates Physical Unclonable Functions (PUFs) for lightweight authentication, an Enhanced Quantified role-based Practical Byzantine Fault Tolerance (EQPBFT) consensus mechanism for efficient and secure block creation, and a Deep Neural Network (DNN)-based intrusion detection system into a unified trust management pipeline. The EQPBFT algorithm improves network resilience by efficiently identifying and mitigating malicious nodes during block creation. In addition, a DNN-based intrusion detection system enhances threat classification and strengthens attack detection accuracy. Simulation results demonstrate reduced computation time (up to 25% lower than PBFT), faster block creation (5.2 ms vs. 6.6 ms for 200 nodes), and higher intrusion detection accuracy (95%) compared to baseline models. These quantitative outcomes validate the robustness and efficiency of the proposed system.

Scientific ReportsVol. 15(1)
University of the Sunshine Coast (AU), Vellore Institute of Technology University (IN)
Vellore Institute of Technology, Chennai, VIT University
Openalex Percentile: Top 22%
Vehicular Ad Hoc Networks (VANETs)
0.73
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