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Secure and Efficient Classification of Trusted and Untrusted Nodes in Wireless Body Area Networks: A Survey of Techniques and Applications

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dc.citedby2
dc.contributor.authorAl Barazanchi I.I.en_US
dc.contributor.authorHashim W.en_US
dc.contributor.authorThabit R.en_US
dc.contributor.authorSekhar R.en_US
dc.contributor.authorShah P.en_US
dc.contributor.authorPenubadi H.R.en_US
dc.contributor.authorid57659035200en_US
dc.contributor.authorid11440260100en_US
dc.contributor.authorid58891173100en_US
dc.contributor.authorid55792622100en_US
dc.contributor.authorid7403284721en_US
dc.contributor.authorid58779587300en_US
dc.date.accessioned2025-03-03T07:46:51Z
dc.date.available2025-03-03T07:46:51Z
dc.date.issued2024
dc.description.abstractThis review examines Wireless Body Area Networks (WBANs) and their safe and efficient trusted and untrusted node categorization. WBAN data transmission must be secure due to the extensive use of wearable devices and the growing importance of health monitoring. This study reviews methods and applications used to verify network nodes? trustworthiness. Through a detailed analysis, we examine WBAN security and efficiency issues, evaluate existing methods, and highlight their strengths and weaknesses. This paper addresses the crucial issue of categorizing nodes as trusted or untrusted in Wireless Body Area Networks. Secure data transfer in WBANs is crucial as wearable gadgets and health monitoring grow more popular. This research aims to thoroughly investigate WBAN node classification methods and applications for safe and efficient classification. This comprehensive research helps identify security and efficiency issues in these networks and evaluate existing methods. This study can benefit academics, practitioners, and stakeholders interested in WBAN development and implementation. The research illuminates the current advances in safe and efficient node classification, enabling experts to improve WBAN security architecture. This study helps build dependable wireless networks for health monitoring and other uses, advancing wearable technology. ? The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1007/978-3-031-62881-8_21
dc.identifier.epage264
dc.identifier.scopus2-s2.0-85198934772
dc.identifier.spage254
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85198934772&doi=10.1007%2f978-3-031-62881-8_21&partnerID=40&md5=cf36c9a02def2aa587a0eb4024994b82
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/37039
dc.identifier.volume1036 LNNS
dc.pagecount10
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.sourceScopus
dc.sourcetitleLecture Notes in Networks and Systems
dc.subjectData transfer
dc.subjectNetwork security
dc.subjectWearable technology
dc.subjectWireless local area networks (WLAN)
dc.subjectClassification technique
dc.subjectEfficiency in wireless body area network
dc.subjectHealth monitoring
dc.subjectNetwork node
dc.subjectNode classification
dc.subjectSecurity in wireless body area network
dc.subjectTrusted node
dc.subjectUntrusted node classification technique
dc.subjectWireless body area network
dc.subjectEfficiency
dc.titleSecure and Efficient Classification of Trusted and Untrusted Nodes in Wireless Body Area Networks: A Survey of Techniques and Applicationsen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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