Authors

Yuvraj Bansal

Department of Computer Science & Engineering, S J M Institute of Technology, Chitradurga, India

Abstract

The rapid evolution of the Internet of Vehicles (IoV) has enabled intelligent transportation systems through real-time vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-everything (V2X) communication. However, the highly distributed and dynamic nature of IoV networks introduces significant challenges related to security, privacy, data integrity, and trust management. Centralized architectures are particularly vulnerable to single points of failure, cyberattacks, data manipulation, and unauthorized access. In this context, Blockchain technology has emerged as a promising decentralized solution capable of enhancing security and transparency within vehicular networks. This comprehensive review examines the role of blockchain in addressing critical IoV security concerns, including authentication, secure data sharing, intrusion detection, privacy preservation, and trust evaluation. The study analyzes various blockchain architectures—public, private, and consortium networks—and evaluates their suitability for vehicular environments. It further explores the integration of smart contracts, consensus mechanisms, and cryptographic protocols to ensure secure communication among vehicles and infrastructure nodes. Additionally, the review highlights current research trends, scalability limitations, latency challenges, and energy efficiency concerns associated with blockchain deployment in real-time vehicular systems. The findings indicate that blockchain-based frameworks significantly improve data integrity, decentralized trust management, and resilience against malicious attacks. However, practical implementation requires optimization strategies to overcome computational overhead and network delay constraints. This review provides a structured understanding of blockchain-enabled IoV security models and outlines future research directions aimed at developing scalable, efficient, and privacy-preserving vehicular communication systems.

Keywords

Blockchain; Internet of Vehicles (IoV); Vehicular Ad Hoc Networks (VANETs); Smart Contracts; Distributed Ledger Technology (DLT); Cybersecurity; Privacy Preservation

Citation of this Article

Yuvraj Bansal. (2025). Machine Learning Approaches to Antique Item Valuation in Online Auction Ecosystems. Journal of Artificial Intelligence and Emerging Technologies. 2(5), 1-7. Article DOI: https://doi.org/10.47001/JAIET/2025.205001

Licence Copyright (c) 2026 Journal of Artificial Intelligence and Emerging Technologies. This work is licensed under a Creative Commons Attribution Non Commercial 4.0 International Licence.

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