Facial and Palm-Based Biometric Authentication and Data Security

Facial and Palm-Based Biometric Authentication and Data Security | 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 Facial and Palm-Based Biometric Authentication and Data Security Chandra Sekhar Tiwari, Vijay Kumar Jha This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4710782/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 Biometric Authentication (BA) is frequently used for authentication owing to its high recognition rate. The existing biometric hiding algorithms execute data embedding on areas that do not encompass key features of the biometric. Moreover, these techniques lacked authorization. Thus, a Secure Data Transfer model with BA and Blockchain (BC)-based authorization is proposed. Primarily, the data owner registers their details and the registered face and palm image undergoes pre-processing. By employing Pruned Residual Network 50 (PRESNET 50), the facial landmarks are extracted from the pre-processed face image. Next, Digit Folding based Log Facial Jaw Points Curve Cryptographic (DF-LFJPCC) is executed based on the jaw points to generate a secret key. Then, the Tan Sigmoid-based Convolutional Neural Network (TS-CNN) classifier is trained with the features of the pre-processed images and facial landmarks. After registration, the user logins, and their processed face and palm features are given to the trained TS-CNN for authenticating the user. The secret is also used to improve the authentication process. After successful login, the file to be uploaded is converted into cipher, which is then encrypted using Log Facial Jaw Points Curve Cryptographic (LFJPCC) and uploaded to the cloud server. In the end, authorization is performed in the BC based on the hashcode generated using Faro shuffle -Tiger (FS-Tiger) when a user requests data. As per the experimental analysis, the proposed technique outperforms prevailing models. Pruned Residual Network 50 (PRESNET 50) Tan Sigmoid-based Convolutional Neural Network (TS-CNN) Reverse Caesar-Rotate 13 (RC-ROT 13) Digit Folding based Log Facial Jaw Points Curve Cryptographic (DF-LFJPCC) Faro shuffle -Tiger (FS-Tiger) and Contrast-Limited Adaptive Histogram Equalization (CLAHE) 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4710782","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":328524602,"identity":"6c5c5efa-3e52-46c6-a202-3bb7cc929a71","order_by":0,"name":"Chandra Sekhar Tiwari","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6UlEQVRIiWNgGAWjYDACZhBhwMzAB6I/ADEbOwEdPDAtbGwMDIwzQFqYCWmB2QXSwswDtxcPsGfnMfxcUWAtzybffOyxza9t8nzMDIwfPubgcxiPseQZg3TDNja2dOPcvtuGbcwMzJIzt+HTwrtBssHgMGMbG4+ZdG7PbUagFjZmXvxaNv8EarEHa7HsuW1PjJZtIFsSwVoYftxOJKzlMP83ywaD9OQ2trQ0yd6G28ltzIzNeP3C3n8s+WbDH2vbfubDxyR+/LltO7+9+eCHj3i0oALGNjDZQKx6EPhDiuJRMApGwSgYKQAAhOlCsFGzjDkAAAAASUVORK5CYII=","orcid":"","institution":"Birla Institute of Technology Mesra","correspondingAuthor":true,"prefix":"","firstName":"Chandra","middleName":"Sekhar","lastName":"Tiwari","suffix":""},{"id":328524603,"identity":"e29b2586-b11f-4e68-8d34-a428dcfdef4c","order_by":1,"name":"Vijay Kumar Jha","email":"","orcid":"","institution":"Birla Institute of Technology Mesra","correspondingAuthor":false,"prefix":"","firstName":"Vijay","middleName":"Kumar","lastName":"Jha","suffix":""}],"badges":[],"createdAt":"2024-07-09 09:21:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4710782/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4710782/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62312660,"identity":"51e1f647-e843-4a55-b6e1-eb4dc279c56f","added_by":"auto","created_at":"2024-08-12 21:33:19","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":633321,"visible":true,"origin":"","legend":"","description":"","filename":"Authentication.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4710782/v1_covered_00e44453-8611-41f1-83c7-4b885c4cf571.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eFacial and Palm-Based Biometric Authentication and Data Security\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Pruned Residual Network 50 (PRESNET 50), Tan Sigmoid-based Convolutional Neural Network (TS-CNN), Reverse Caesar-Rotate 13 (RC-ROT 13), Digit Folding based Log Facial Jaw Points Curve Cryptographic (DF-LFJPCC), Faro shuffle -Tiger (FS-Tiger) and Contrast-Limited Adaptive Histogram Equalization (CLAHE)","lastPublishedDoi":"10.21203/rs.3.rs-4710782/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4710782/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBiometric Authentication (BA) is frequently used for authentication owing to its high recognition rate. The existing biometric hiding algorithms execute data embedding on areas that do not encompass key features of the biometric. Moreover, these techniques lacked authorization. Thus, a Secure Data Transfer model with BA and Blockchain (BC)-based authorization is proposed. Primarily, the data owner registers their details and the registered face and palm image undergoes pre-processing. By employing Pruned Residual Network 50 (PRESNET 50), the facial landmarks are extracted from the pre-processed face image. Next, Digit Folding based Log Facial Jaw Points Curve Cryptographic (DF-LFJPCC) is executed based on the jaw points to generate a secret key. Then, the Tan Sigmoid-based Convolutional Neural Network (TS-CNN) classifier is trained with the features of the pre-processed images and facial landmarks. After registration, the user logins, and their processed face and palm features are given to the trained TS-CNN for authenticating the user. 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