An approach to preventing vehicular ad-hoc networks from malicious nodes based on blockchain

Azath M () and Vaishali Singh ()

Review of Computer Engineering Research, 2023, vol. 10, issue 1, 16-27

Abstract: This study presents a revolutionary blockchain-based security mechanism that authenticates vehicles and instantly alerts other vehicles to unlawful messages. Access should only be allowed to authenticated vehicles in order to increase the network security, and access should be restricted or revoked for any vehicles that exhibit inappropriate behaviour. Vehicles linked to the Vehicular Ad Hoc Network (VANET) can share data and take immediate action with the help of adjacent infrastructure devices, like streetlights and traffic signals, as well as with one another. In order to maintain efficiency and safety, an intelligent transportation system depends on the flow of information between vehicles. Intelligent vehicles are vulnerable to hacking attacks because they have numerous technical flaws. A proposed security scheme identifies malicious nodes and detects forged messages, based on multiple factors like sender reputation, time and distance effectiveness. This is accomplished by employing environmental sensory data and authenticating the packets, allowing a vehicle to add numerous blocks to the blockchain. Research has been conducted on the bases of safety protection for vehicle systems as a result of security concerns. When the proposed approach is tested on different vehicle and attacker densities, the results indicate that it has a lower authentication delay and higher communication overhead than the other existing approaches. This study explored various threats from malicious nodes and the techniques in which our proposed methodology handles such attacks.

Keywords: Blockchain; Dynamic vehicular network; Intelligent transportation system Internet of vehicle; Intelligent vehicles; Internet of things sensors; Intrusion detection system; Malicious nodes; Security attacks; Vehicular ad hoc network. (search for similar items in EconPapers)
Date: 2023
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