Energy-efficient multi factor authentication protocols in sustainable security for wireless networks using machine learning algorithm Article Swipe
YOU?
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· 2025
· Open Access
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· DOI: https://doi.org/10.1016/j.rineng.2025.107196
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 %.
Related Topics
- Type
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- https://doi.org/10.1016/j.rineng.2025.107196
- OA Status
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- OpenAlex ID
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4414104699Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.rineng.2025.107196Digital Object Identifier
- Title
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Energy-efficient multi factor authentication protocols in sustainable security for wireless networks using machine learning algorithmWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-09-11Full publication date if available
- Authors
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Radha Raman Chandan, Hemalatha Thanganadar, Upendra N. Dwivedi, Surendra Kumar Shukla, Shreyas Pagare, Navruzbek ShavkatovList of authors in order
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https://doi.org/10.1016/j.rineng.2025.107196Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1016/j.rineng.2025.107196Direct OA link when available
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0Total citation count in OpenAlex
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22Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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