TADM: A Trust-Aware and Drift-Adaptive Framework for Intelligent Data Management

TADM: A Trust-Aware and Drift-Adaptive Framework for Intelligent Data Management | 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 TADM: A Trust-Aware and Drift-Adaptive Framework for Intelligent Data Management Hemn Barzan Abdalla, Davide Tosic This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9361575/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Data management systems increasingly operate in dynamic environments where data distributions evolve continuously, and privacy risks are unpredictable. Most existing methods rely on static trust assumptions and threshold-based drift detection, leading to unstable governance decisions, delayed risk mitigation, and unnecessary utility loss. We propose a Trust-Aware and Drift-Adaptive Framework for Intelligent Data Management (TADM), which integrates a trust-aware and drift-adaptive data management framework that integrates dynamic trust modeling, soft drift awareness, and multi-objective optimization within a closed-loop control architecture. Trust is modeled as a time-dependent system state that jointly reflects data reliability, consistency under drift, and privacy risk, with drift severity incorporated directly into governance objectives through smooth, non-threshold-based penalties. TADM using both simulated data streams and a real-world dataset of NYC taxi trips. In synthetic experiments, TADM achieves stable governance, measured by fewer than one policy switch on average and a policy churn rate of 0.011, with fewer than one policy switch on average while preserving over 40% utility under moderate drift and degrading gracefully under severe drift. In the real-world case study, TADM achieves a mean trust level of 0.69, stable non-oscillatory policies, and over 63% utility, despite persistent non-stationarity, without requiring labeled drift events or manual intervention. Concept drift Trust-aware data management Adaptive governance Privacy-utility trade-off Intelligent Data Management Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 14 Apr, 2026 Reviewers invited by journal 09 Apr, 2026 Editor assigned by journal 09 Apr, 2026 Submission checks completed at journal 09 Apr, 2026 First submitted to journal 08 Apr, 2026 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-9361575","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":623630266,"identity":"67819044-c4b9-4882-b597-4d0acf765e8f","order_by":0,"name":"Hemn Barzan Abdalla","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyElEQVRIiWNgGAWjYBACAwYeBgmGAgsGfh6IAGMDcVoMJBgke0jWYnCGWC3m7GcP3vhhICFvfObwwc8FDDayGw4Q0GLZk5ds2WMgYbjtbFuy9AyGNGOCWgwO5JhJ8BhIMG47z2MgzcNwOJGwlvNvzCT/GEjYb+7n//ybh+E/EVpu5JhJA21J3MDbwwa05QAxWt4lW8sYSCTPOHPMzJrHINl4JmGH5R68+abCxra/J/nxbZ4KO9k+QlrQTSBN+SgYBaNgFIwCHAAArmBAkxOCInYAAAAASUVORK5CYII=","orcid":"","institution":"Wenzhou-Kean University","correspondingAuthor":true,"prefix":"","firstName":"Hemn","middleName":"Barzan","lastName":"Abdalla","suffix":""},{"id":623630267,"identity":"997371f0-2813-4bf2-8083-3ec9c25d5517","order_by":1,"name":"Davide Tosic","email":"","orcid":"","institution":"University of Insubria","correspondingAuthor":false,"prefix":"","firstName":"Davide","middleName":"","lastName":"Tosic","suffix":""}],"badges":[],"createdAt":"2026-04-09 00:23:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9361575/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9361575/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107482926,"identity":"ef84bd17-8640-484b-a359-8cc4d3a3a1f2","added_by":"auto","created_at":"2026-04-22 02:25:37","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":679598,"visible":true,"origin":"","legend":"","description":"","filename":"Article.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9361575/v1_covered_ec054926-885f-4bec-9358-2a016894d056.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"TADM: A Trust-Aware and Drift-Adaptive Framework for Intelligent Data Management","fulltext":[],"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":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"knowledge-and-information-systems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"kais","sideBox":"Learn more about [Knowledge and Information Systems](http://link.springer.com/journal/10115)","snPcode":"10115","submissionUrl":"https://submission.nature.com/new-submission/10115/3","title":"Knowledge and Information Systems","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Concept drift, Trust-aware data management, Adaptive governance, Privacy-utility trade-off, Intelligent Data Management","lastPublishedDoi":"10.21203/rs.3.rs-9361575/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9361575/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eData management systems increasingly operate in dynamic environments where data distributions evolve continuously, and privacy risks are unpredictable. 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