Abstract
The rapid growth and technological progressions in the vehicle edge computing and networks (VECON) enhanced existing vehicular administrations through information sharing and information investigation, which further incremented traffic security difficulties. This carries the need to verify vehicle networks with gigantic information stockpiling substances. Recognizing the vehicles that communicate fashioned messages and ensuring the protection of every vehicle is an essential assignment. Blockchain can be utilized as an effective solution to provide security during vehicle edge computing. Every transaction and data is recorded in the blockchain, which expands the number of blocks after some time. Another test in blockchain methods is utilizing a consensus mechanism, which can be effectively undermined by the attackers. Artificial intelligence (AI) trained by machine learning (ML) algorithms as an amazing paradigm can be incorporated with blockchain to settle these issues. The data storing methods of blockchain can likewise be enhanced with the assistance of ML algorithms. In this paper, a two-tier authenticated consortium blockchain (TTA-CB) protocol is proposed for secure information partaking in Vehicle Edge Computing and Networks (VECONs). Utilizing a one-time password (OTP) based notoriety estimation calculation, the misbehaving vehicles are recognized. The use of Particle Swarm Optimization (PSO) understands the ideal data provider selection issue utilizing notoriety esteems. Exploratory outcomes demonstrate the importance of the proposed strategy, and the correlation results demonstrate that the proposed technique is unrivaled and secure.
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This article is part of the Topical Collection: Special Issue on Blockchain for Peer-to-Peer Computing
Guest Editors: Keping Yu, Chunming Rong, Yang Cao, and Wenjuan Li
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Gawas, M., Patil, H. & Govekar, S.S. An integrative approach for secure data sharing in vehicular edge computing using Blockchain. Peer-to-Peer Netw. Appl. 14, 2840–2857 (2021). https://doi.org/10.1007/s12083-021-01107-4
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DOI: https://doi.org/10.1007/s12083-021-01107-4