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Augmenting Vehicular Ad Hoc Network Security and Efficiency with Blockchain: A Probabilistic Identification and Malicious Node Mitigation Strategy

Publicat a:Electronics. 12 (23): 4794- - 2023-12-01 12(23), DOI: 10.3390/electronics12234794

Autors: Juarez, Ruben; Bordel, Borja

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This manuscript delineates the development of an avant garde dual-layer blockchain architecture, which has been meticulously engineered to augment the security and operational efficacy of vehicular ad hoc networks (VANETs). VANETs, which are integral to the infrastructure of intelligent transport systems, facilitate the critical exchange of information between vehicular nodes. Despite their significance, these networks confront an array of formidable security vulnerabilities. Our innovative approach, employing a dual blockchain framework-the event chain and the reputation chain-meticulously tracks network activities, thereby significantly enhancing the trustworthiness and integrity of the system. This research presents a transformative dual-layer blockchain architecture, which was conceived to address the intricate security challenges pervasive in VANETs. The architecture pivots on a sophisticated reputation assessment framework, thus leveraging the principles of Bayesian inference and the analytical rigor of historical data to markedly diminish observational errors, as well as elevate the accuracy of reputation evaluations for vehicular nodes. A salient feature of our methodology is the implementation of an attenuation factor, which has been deftly calibrated to modulate the impact of historical behaviors on current reputation scores, thereby ensuring their relevance and alignment with recent vehicular interactions. Additionally, the numerical threshold serves as an indispensable mechanism, thus establishing a definitive criterion for the early identification of potentially malicious activities and enabling the activation of proactive security measures to safeguard the network's integrity. Empirical validation of our dual-layer blockchain model has yielded a remarkable 86% efficacy in counteracting malevolent behaviors, thus significantly outperforming extant paradigms. These empirical outcomes underscore the model's potential as a vanguard in the domain of secure and efficient reputation management within VANETs, thereby heralding a substantial advancement in the sphere of intelligent transportation systems.

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