Affiliation:
1. Assistant Professor, Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India
2. Professor, Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India
Abstract
SummaryOne of the key strategies in wireless sensor network (WSN) for sending data packets to the base station (BC) is known as routing. However, malicious node outbreaks will occur, which exaggerate the functions of WSNs during the routing procedure. A secure routing protocol is necessary to protect the effectiveness of WSN and routing fortification. In real‐time scenarios, the existing routing protocol is volatile dynamically; it makes difficult to identify the performance of unprotected routing nodes. In this manuscript, a unique routing strategy is proposed for secured dynamic optimal routing (SDOR) in WSN that combines block chain technology optimized with a generative adversarial capsule network. Every routing sensor node contains a secret key, which is used to construct a crypto hash signature (CHS) token for flow access. The proposed block chain‐based WSN is used to provide SDOR information using a self‐attention‐based generative adversarial capsule network that is improved using the flamingo search algorithm. Following that, the security on the proposed block chain WSN is assessed from six angles. Block chain token transactions are evaluated using measures including average latency, average energy usage, and throughput. The proposed SDOR‐SA‐GAC‐FSA‐CHS‐BWSN delivers 53.87%, 42.57%, and 32.87% lower average packet delay, 28.97%, 37.73%, and 34.75% lesser identification time analyzed to the existing methods, such as trusted distributed routing scheme for WSNs using block chain (SDOR‐DCNN‐SSOA‐BWSN), secure authentication with DSM‐KL ascertained presentation optimization of hybrid block chain‐enabled model for multi‐WSN (SDOR‐DSM‐KL‐BWSN), and optimizing the valid transaction utilizing reinforcement learning‐based block chain ecosystem in WSN (SDOR‐RIL‐BWSN).
Subject
Electrical and Electronic Engineering,Computer Networks and Communications