Auto-metric Graph Neural Network based Blockchain Technology for Secured Dynamic Optimal Routing in MANET

Auto-metric Graph Neural Network based Blockchain Technology for Secured Dynamic Optimal Routing in MANET

Автор: Francis H. Shajin, Muthusamy Palaniappan, P. Rajesh

Журнал: International Journal of Computer Network and Information Security @ijcnis

Статья в выпуске: 1 vol.16, 2024 года.

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Mobile ad hoc network (MANET) routing is a generous tactic used for allocating packets to the base station (BS). During the operations of routing, occurrence of malicious node embellishes the mobile ad hoc network operations. For that reason, a trusted distributed routing protocol is obliged that maintains the routing buttressing and the proficiency of mobile ad hoc network. To overcome these challenging issues, Auto-Metric Graph Neural Network based Blockchain technology is proposed in this manuscript for Secured Dynamic Optimal Routing in MANET (BC-SDOR-MANET-AGNN). The proposed approach is simulated in NS-2 tool. The proposed BC-SDOR-MANET-AGNN approach attains 76.26%, 65.57%, 42.9% minimal delay during 25% malicious routing environment, 73.06%, 63.82%, 38.84% less delay during 50% malicious routing environment when analyzed to the existing models, like enhanced hybrid secure multipath routing protocol for MANET (BC-SDOR-MANET-GAHC), an improved ad hoc on-demand distance vector routing security approach based on BC technology in MANET (BC-SDOR-MANET-AODV-MQS) and block chain-based better approach for the mobile ad-hoc networking protocol using ensemble algorithm (BC-SDOR-MANET-E-BATMAN) methods.

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Auto-metric Graph Neural Network, Block Chain Technology, Malicious Node Attacks Mobile ad Hoc Network, Trusted Distributed Routing Protocol

Короткий адрес: https://sciup.org/15018826

IDR: 15018826   |   DOI: 10.5815/ijcnis.2024.01.10

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