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Article type: Research Article
Authors: Anitha, R.a | Bapu, B.R. Tapasb; *
Affiliations: [a] Faculty of Computer Applications (MCA), S. A. Engineering College, Chennai, India | [b] Faculty of Electronics and Communication Engineering, S. A. Engineering College, Chennai, India
Correspondence: [*] Corresponding author. B.R. Tapas Bapu, Professor, Faculty of Electronics and Communication Engineering, S. A. Engineering College, Chennai, India. E-mail: drtapasbapubrphd@gmail.com.
Abstract: In wireless sensor network (WSN), routing is one of the substantial maneuvers for distributing data packets to the base station. But malevolent node outbreaks will happen during routing process, which exaggerate the wireless sensor network operations. Therefore, a secure routing protocol is required, which safeguards the routing fortification and the wireless sensor network effectiveness. The existing routing protocol is dynamically volatile during real time instances, and it is very hard to recognize the unsecured routing node performances. In this manuscript, a Deep Dropout extreme Machine learning optimized Improved Alpha-Guided Grey Wolf based Crypto Hash Signature Token fostered Blockchain Technology is proposed for secure dynamic optimal routing in Wireless Sensor Networks (SDOR-DEML-IAgGWO-CHS-BWSN). In this, Crypto Hash signature (CHS) token are generated for flow accesses with a secret key owned by each routing sensor node and it also offers an optimal path for data transmission. Then the secured dynamic optimal routing information is delivered through the proposed Blockchain based wireless sensor network platform with the help of Deep Dropout Extreme Machine learning optimized Improved Alpha-Guided Grey Wolf routing algorithm. Then the proposed method is simulated using the NS-2 (Network Simulator) tool. The simulation performance of the proposed SDOR-DEML-IAgGWO-CHS-BWSN method provide 76.26%, 65.57%, 60.85%, 48.99% and 42.9% lower delay during 30% malicious routing environment, 73.06%, 63.82%, 59.25%, 44.79% and 38.84% lower delay during 60% malicious routing environment is compared with the existing methods.
Keywords: Wireless sensor network, secured routing protocol, malicious node attacks, Deep Dropout extreme machine learning, Improved Alpha-Guided Grey Wolf, Crypto Hash Signature token, blockchain technology
DOI: 10.3233/JIFS-212455
Journal: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7525-7543, 2022
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