Hybrid key management WSN protocol to enhance network performance using ML Techniques for IoT application in cloud Environment

Hybrid key management WSN protocol to enhance network performance using ML Techniques for IoT application in cloud Environment | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Hybrid key management WSN protocol to enhance network performance using ML Techniques for IoT application in cloud Environment Raghini M, Selvam Durairaj, Sasikala S, Appavu alias Balamurugan S This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4386861/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract As the Internet of Things (IoT) develops, Wireless Sensor Networks (WSNs) must be used to collect and transmit critical data. Ensuring the security and efficiency of these networks is paramount, given the sheer volume and sensitivity of the data they handle. This paper introduces a novel hybrid key management protocol for WSNs in IoT applications, integrating cloud services and harnessing Machine Learning (ML) techniques to enhance network performance and security. The proposed hybrid key management protocol leverages the strengths of symmetric and asymmetric essential management methods, providing a robust foundation for securing communication within the WSN. It also capitalizes on cloud-based services’ scalability and centralized management capabilities to streamline key distribution and facilitate network-wide updates. Machine Learning techniques are seamlessly integrated into the protocol, enabling predictive key distribution, anomaly detection, dynamic key management, and intelligent network load balancing. By analyzing historical data and network patterns, ML algorithms predict optimal times and locations for critical updates, reducing overhead and enhancing security. Additionally, ML-based anomaly detection empowers the protocol to identify and respond to network irregularities and potential security breaches. This framework combines centralized key management, cloud integration, and the intelligence of Machine Learning, resulting in a highly adaptable and efficient protocol for IoT-enabled WSNs. The network performance is enhanced by using exiting techniques and algorithms. Hybrid key cluster head encryption throughput ML-based security IoT application Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4386861","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":302109451,"identity":"6bef7ee1-806b-404d-a7d0-d5092f71c754","order_by":0,"name":"Raghini M","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAnklEQVRIiWNgGAWjYHACxgdwZgKRWpgNgIQESVrYJOBaiAK6s0+nVfPU2NQxsB9+wPBwBxFazM7lbrvNcyxNgoEnzYAh8QwxWs7wbrs5s+Ew0GE5DAyJbURqKZzZ8F+Cgf8NCVoYPjYckGCQIMGWzRIfjiVLtkk8MzhArJaNHxJq7Pj5+ZMfPvxJjBY4YAPiA6RoGAWjYBSMglGABwAAyakwqzQOTokAAAAASUVORK5CYII=","orcid":"","institution":"Velammal College of Engineering and Technology","correspondingAuthor":true,"prefix":"","firstName":"Raghini","middleName":"","lastName":"M","suffix":""},{"id":302109452,"identity":"2a7c8af5-5964-4adf-a561-b43472ea6bb6","order_by":1,"name":"Selvam Durairaj","email":"","orcid":"","institution":"VIT Chennai","correspondingAuthor":false,"prefix":"","firstName":"Selvam","middleName":"","lastName":"Durairaj","suffix":""},{"id":302109453,"identity":"4742673f-2bd5-4084-a557-aad627745fff","order_by":2,"name":"Sasikala S","email":"","orcid":"","institution":"Velammal College of Engineering and Technology","correspondingAuthor":false,"prefix":"","firstName":"Sasikala","middleName":"","lastName":"S","suffix":""},{"id":302109454,"identity":"cd9f0303-47ad-4862-98ad-87fb5c9de43f","order_by":3,"name":"Appavu alias Balamurugan S","email":"","orcid":"","institution":"Periyar Maniammai Institute of Science \u0026 Technology (Deemed to be University)","correspondingAuthor":false,"prefix":"","firstName":"Appavu","middleName":"alias Balamurugan","lastName":"S","suffix":""}],"badges":[],"createdAt":"2024-05-08 06:12:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4386861/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4386861/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":59523131,"identity":"bed191e9-a845-46e2-8ca2-63d701fcbbd8","added_by":"auto","created_at":"2024-07-02 20:34:29","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2056099,"visible":true,"origin":"","legend":"","description":"","filename":"MAINDOCUMENT.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4386861/v1_covered_db751096-70e4-4310-97df-2856685b5b51.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Hybrid key management WSN protocol to enhance network performance using ML Techniques for IoT application in cloud Environment","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Hybrid key, cluster head, encryption throughput, ML-based security, IoT application","lastPublishedDoi":"10.21203/rs.3.rs-4386861/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4386861/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAs the Internet of Things (IoT) develops, Wireless Sensor Networks (WSNs) must be used to collect and transmit critical data. 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