Enhanced Elman Spike Neural Network optimized with Glowworm Swarm Optimization for Authentication of Multiple Transaction using Finger Vein

Enhanced Elman Spike Neural Network optimized with Glowworm Swarm Optimization for Authentication of Multiple Transaction using Finger Vein | 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 Enhanced Elman Spike Neural Network optimized with Glowworm Swarm Optimization for Authentication of Multiple Transaction using Finger Vein S. Mary Joans, J.S. Leena Jasmine, P. Ponsudha This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1775418/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract Nowadays, Automated Teller Machines (ATM) are broadly used every one Hence, the security is some more need to improve the bank sector. Due to increase in the count of criminals and their activities, ATMs have become unsafe. The access card and PIN are used in the ATM system for identity verification. Recent advances in biometric detection techniques, like fingerprinting, retinal scanning, face recognition, have made great strides in recovering the insecure environment at ATMs. In this manuscript, an Enhanced Elman Spike Neural Network Optimized with Glowworm Swarm Optimization is proposed for Authentication of Multiple Transaction Using Finger Vein (EESNN-GWO-AMT-FV). Here finger vein authentication, images are collected from the SDUMLA-HMT dataset. Then the images are pre-processed to improve the quality of the images using contrast limited adaptive histogram equalization filtering (CLAHEF).The features are extracted by using the visual geometry group network (VGG16).By using VGG16 model, various features are extracted, such as Vein Patterns, Local Binary Patterns, Dimensionality Reduction andImage Transformations. The extracted features are transferred to EESNN classifier for classifying the authorized person and unauthorized person. Then the weight parameters of the EESNN are optimized using the Glowworm swarm optimization Algorithm (GWO). The proposed method is implemented and the efficiency of the proposed EESNN-GWO-AMT-FV is examined under performance metrics, viz accuracy, specificity, sensitivity, precision, Error rate, AUC. The performance of the proposed method provides higher accuracy 99.01%, 98.34%, and 97.45%, and higher precision 87.12%, 94.12% and 91.78% compared with existing methods, like CNN-AOA-MBR-FV, CNN-MBR-FKP-FV and DCNN-MBR-FV respectively. Authentication Of Multiple Transaction contrast limited adaptive histogram equalization filtering Enhanced Elman Spike Neural Network Finger Vein Glowworm Swarm Optimization visual geometry group network Full Text Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 21 Jun, 2022 Editor assigned by journal 21 Jun, 2022 First submitted to journal 19 Jun, 2022 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-1775418","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":115333294,"identity":"dded19bd-34c2-4395-96a8-f65b1bd72ad3","order_by":0,"name":"S. Mary Joans","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABK0lEQVRIie2QMUvDQBTHEw4uy4tdTyLWj3ASSBoK+lWUQKYrOgpKm1LIVOuq36LTzQmH6RL3gGPAoVMhIBSDmKtYFJLiKHi/4d2fx/vBe6dpCsUfZfX5xLIQdLqYyEQOdhj6/TelZ2hZeiYV+IWy4aqj5YzK1Kq4lkjGa3ZyQRORlJcVsfSQlcv8pgeaIR7nDYo3C84nJve9eZz61kNEbKQ98T5L68UgCPIGhWbgFjpHlMYZtcyQ+Fi/5TbDtULAaVGOx2s+kor9BhUZTRG82Ox9txKaXEjFsQATRDCgYhC1K94Uy1sWdD9Og74ZEUQBO2gwI4BbbnEB1T/Gr+leLsQzVENEu0VRstfhYccQaeNiX+Eoj7dNTDa1YfyH0r0Lt020aplWKBSK/8kHMddkp/BQn3YAAAAASUVORK5CYII=","orcid":"","institution":"Velammal Engineering College","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"S.","middleName":"Mary","lastName":"Joans","suffix":""},{"id":115333295,"identity":"f147ae4f-a417-4ca9-bb46-25ac96fa78f4","order_by":1,"name":"J.S. Leena Jasmine","email":"","orcid":"","institution":"Velammal Engineering College","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"J.S.","middleName":"Leena","lastName":"Jasmine","suffix":""},{"id":115333296,"identity":"bd6a15a0-7e43-4855-bd7f-47b55694c11d","order_by":2,"name":"P. Ponsudha","email":"","orcid":"","institution":"Anna University Chennai","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"P.","middleName":"","lastName":"Ponsudha","suffix":""}],"badges":[],"createdAt":"2022-06-20 07:19:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1775418/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1775418/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":23237084,"identity":"b0b1a03b-ec8a-469a-9263-9439206b3ece","added_by":"auto","created_at":"2022-06-29 15:54:14","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":707809,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1775418/v1_covered.pdf"}],"financialInterests":"","formattedTitle":"Enhanced Elman Spike Neural Network optimized with Glowworm Swarm Optimization for Authentication of Multiple Transaction using Finger Vein","fulltext":[{"header":"Full Text","content":"This preprint is available for \u003ca href='/article/rs-1775418/latest.pdf' target='_blank'\u003edownload as a PDF\u003c/a\u003e."}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"wireless-personal-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wire","sideBox":"Learn more about [Wireless Personal Communications](https://www.springer.com/journal/11277)","snPcode":"11277","submissionUrl":"https://submission.nature.com/new-submission/11277/3","title":"Wireless Personal Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Authentication Of Multiple Transaction, contrast limited adaptive histogram equalization filtering, Enhanced Elman Spike Neural Network, Finger Vein, Glowworm Swarm Optimization, visual geometry group network","lastPublishedDoi":"10.21203/rs.3.rs-1775418/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1775418/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNowadays, Automated Teller Machines (ATM) are broadly used every one Hence, the security is some more need to improve the bank sector. Due to increase in the count of criminals and their activities, ATMs have become unsafe. The access card and PIN are used in the ATM system for identity verification. Recent advances in biometric detection techniques, like fingerprinting, retinal scanning, face recognition, have made great strides in recovering the insecure environment at ATMs. In this manuscript, an Enhanced Elman Spike Neural Network Optimized with Glowworm Swarm Optimization is proposed for Authentication of Multiple Transaction Using Finger Vein (EESNN-GWO-AMT-FV). Here finger vein authentication, images are collected from the SDUMLA-HMT dataset. Then the images are pre-processed to improve the quality of the images using contrast limited adaptive histogram equalization filtering (CLAHEF).The features are extracted by using the visual geometry group network (VGG16).By using VGG16 model, various features are extracted, such as Vein Patterns, Local Binary Patterns, Dimensionality Reduction andImage Transformations. The extracted features are transferred to EESNN classifier for classifying the authorized person and unauthorized person. Then the weight parameters of the EESNN are optimized using the Glowworm swarm optimization Algorithm (GWO). The proposed method is implemented and the efficiency of the proposed EESNN-GWO-AMT-FV is examined under performance metrics, viz accuracy, specificity, sensitivity, precision, Error rate, AUC. The performance of the proposed method provides higher accuracy 99.01%, 98.34%, and 97.45%, and higher precision 87.12%, 94.12% and 91.78% compared with existing methods, like CNN-AOA-MBR-FV, CNN-MBR-FKP-FV and DCNN-MBR-FV respectively.\u003c/p\u003e","manuscriptTitle":"Enhanced Elman Spike Neural Network optimized with Glowworm Swarm Optimization for Authentication of Multiple Transaction using Finger Vein","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-06-29 15:54:06","doi":"10.21203/rs.3.rs-1775418/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2022-06-21T15:14:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-06-21T04:34:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"Wireless Personal Communications","date":"2022-06-20T03:18:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"wireless-personal-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wire","sideBox":"Learn more about [Wireless Personal Communications](https://www.springer.com/journal/11277)","snPcode":"11277","submissionUrl":"https://submission.nature.com/new-submission/11277/3","title":"Wireless Personal Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"f06b1aa4-edd6-43cd-ae26-a51fd4cc1160","owner":[],"postedDate":"June 29th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-06-29T15:54:07+00:00","versionOfRecord":[],"versionCreatedAt":"2022-06-29 15:54:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1775418","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1775418","identity":"rs-1775418","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}