​​August 2021, Vol. 6, No. 8, pp. 147-153. 

​​​Neighbour node trust identification using cluster approach in VANET

R. Kethsiyal Majella*, S. Sumithra
Department of Electronics and Communication Engineering, JJ College of Engineering and Technology, Trichy. Tamilnadu, India.

​​​*Corresponding author’s e-mail: kethsi11@gmail.com

​Abstract

​The dynamic nature of vehicular networks imposes plenty of challenges in multi hop data transmission as links are vulnerable in their existence because of associated mobility of vehicles. Thus, packets frequently find it difficult to induce through to the destination having the limited lifetimes of links. Vehicular Ad-hoc Network (VANET), a novel technology holds a paramount importance within the transportation domain due to its abilities to increase traffic efficiency and safety. However, VANET can also include dishonest nodes like Man-in-the-Middle (MiTM) attackers getting to distribute and share malicious content with the vehicles, thus polluting the network with compromised information. In this regard, establishing trust among connected vehicles can increase security as every participating vehicle will generate and propagate authentic, accurate and trusted content within the network. In this paper propose a unique trust model, namely, Man-in-the-middle Attack Resistance trust model in connected vehicles (MARINE), which identifies dishonest nodes performing MiTM attacks in an efficient way also as revokes their credentials. Every node running MARINE system first establishes trust for the sender by performing multi-dimensional plausibility checks. Once the receiver verifies the trustworthiness of the sender, the received data is then evaluated both directly and indirectly. Extensive simulations are carried out to evaluate the performance and routing framework of MARINE rigorously in terms of the performance over the existing scheme models and the trust model.

Keywords: Vehicular Ad-hoc Network; Trust Model; Man-in-the-Middle; Resistance trust model.

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International Journal of Modern Science and Technology

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ISSN 2456-0235