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NeoStarling: An Efficient and Scalable Collaborative Blockchain-Enabled Obstacle Mapping Solution for Vehicular Environments

The Vehicular Self-Organizing Network (VANET) is a burgeoning research topic within Intelligent Transportation Systems, holding promise in enhancing safety and convenience for drivers. In general, VANETs require large amounts of data to be shared among vehicles within the network. But then two chall...

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Detalles Bibliográficos
Autores principales: Juárez, Rubén, Bordel, Borja
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490777/
https://www.ncbi.nlm.nih.gov/pubmed/37687956
http://dx.doi.org/10.3390/s23177500
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author Juárez, Rubén
Bordel, Borja
author_facet Juárez, Rubén
Bordel, Borja
author_sort Juárez, Rubén
collection PubMed
description The Vehicular Self-Organizing Network (VANET) is a burgeoning research topic within Intelligent Transportation Systems, holding promise in enhancing safety and convenience for drivers. In general, VANETs require large amounts of data to be shared among vehicles within the network. But then two challenges arise. First, data security, privacy, and reliability need to be ensured. Second, data management and security solutions must be very scalable, because current and future transportation systems are very dense. However, existing Vehicle-to-Vehicle solutions fall short of guaranteeing the veracity of crucial traffic and vehicle safety data and identifying and excluding malicious vehicles. The introduction of blockchain technology in VANETs seeks to address these issues. But blockchain-enabled solutions, such as the Starling system, are too computationally heavy to be scalable enough. Our proposed NeoStarling system focuses on proving a scalable and efficient secure and reliable obstacle mapping using blockchain. An opportunistic mutual authentication protocol, based on hash functions, is only triggered when vehicles travel a certain distance. Lightweight cryptography and an optimized message exchange enable an improved scalability. The evaluation results show that our collaborative approach reduces the frequency of authentications and increases system efficiency by 35%. In addition, scalability is improved by 50% compared to previous mechanisms.
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spelling pubmed-104907772023-09-09 NeoStarling: An Efficient and Scalable Collaborative Blockchain-Enabled Obstacle Mapping Solution for Vehicular Environments Juárez, Rubén Bordel, Borja Sensors (Basel) Article The Vehicular Self-Organizing Network (VANET) is a burgeoning research topic within Intelligent Transportation Systems, holding promise in enhancing safety and convenience for drivers. In general, VANETs require large amounts of data to be shared among vehicles within the network. But then two challenges arise. First, data security, privacy, and reliability need to be ensured. Second, data management and security solutions must be very scalable, because current and future transportation systems are very dense. However, existing Vehicle-to-Vehicle solutions fall short of guaranteeing the veracity of crucial traffic and vehicle safety data and identifying and excluding malicious vehicles. The introduction of blockchain technology in VANETs seeks to address these issues. But blockchain-enabled solutions, such as the Starling system, are too computationally heavy to be scalable enough. Our proposed NeoStarling system focuses on proving a scalable and efficient secure and reliable obstacle mapping using blockchain. An opportunistic mutual authentication protocol, based on hash functions, is only triggered when vehicles travel a certain distance. Lightweight cryptography and an optimized message exchange enable an improved scalability. The evaluation results show that our collaborative approach reduces the frequency of authentications and increases system efficiency by 35%. In addition, scalability is improved by 50% compared to previous mechanisms. MDPI 2023-08-29 /pmc/articles/PMC10490777/ /pubmed/37687956 http://dx.doi.org/10.3390/s23177500 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Juárez, Rubén
Bordel, Borja
NeoStarling: An Efficient and Scalable Collaborative Blockchain-Enabled Obstacle Mapping Solution for Vehicular Environments
title NeoStarling: An Efficient and Scalable Collaborative Blockchain-Enabled Obstacle Mapping Solution for Vehicular Environments
title_full NeoStarling: An Efficient and Scalable Collaborative Blockchain-Enabled Obstacle Mapping Solution for Vehicular Environments
title_fullStr NeoStarling: An Efficient and Scalable Collaborative Blockchain-Enabled Obstacle Mapping Solution for Vehicular Environments
title_full_unstemmed NeoStarling: An Efficient and Scalable Collaborative Blockchain-Enabled Obstacle Mapping Solution for Vehicular Environments
title_short NeoStarling: An Efficient and Scalable Collaborative Blockchain-Enabled Obstacle Mapping Solution for Vehicular Environments
title_sort neostarling: an efficient and scalable collaborative blockchain-enabled obstacle mapping solution for vehicular environments
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490777/
https://www.ncbi.nlm.nih.gov/pubmed/37687956
http://dx.doi.org/10.3390/s23177500
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