Energy-efficient multi factor authentication protocols in sustainable security for wireless networks using machine learning algorithm
Аннотация
• Aim of this research is to propose novel method in wireless network security analysis with energy efficiency analysis using machine learning algorithm. • In this research the security analysis for wireless network is carried out using lightweight cryptographic key agreement mutual authentication protocol. • Then the network energy efficiency is carried out using deep gradient descent multilayer Marquardt vector algorithm. • As a result, there is a lot of interest in seeing how to increase WSN energy efficiency while improving security performance. Given the limited energy resources and broadcast nature of wireless communication, the primary problems in wireless sensor networks (WSNs) are energy efficiency and security. As a result, there is a lot of interest in seeing how to increase WSN energy efficiency while improving security performance. Aim of this research is to propose novel method in wireless network security analysis with energy efficiency analysis using machine learning algorithm. In this research the security analysis for wireless network is carried out using lightweight cryptographic key agreement mutual authentication protocol. Then the network energy efficiency is carried out using deep gradient descent multi-layer Marquardt vector algorithm. Experimental analysis is carried out based on network energy efficiency analysis and security analysis in terms of throughput, latency, packet delivery ratio (PDR), energy efficiency, end-end delay. through performance analysis, new protocol is shown to be more efficient than other multi-factor mutual authentication protocol. The proposed model attained Throughput of 97%, PDR of 93%, energy efficiency of 96%, latency of 95%, End-end delay of 94%.