TrustDS: A Policy‑First, Privacy‑Preserving Framework for Interoperable Data Exchange with Real‑World Validation

TrustDS: A Policy‑First, Privacy‑Preserving Framework for Interoperable Data Exchange with Real‑World Validation | 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 TrustDS: A Policy‑First, Privacy‑Preserving Framework for Interoperable Data Exchange with Real‑World Validation Tirupati Rao Dockara, Manisha Malhotra This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7519920/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 We present TrustDS, a policy‑first, privacy‑preserving framework for interoperable data exchange across edge and multi‑cloud environments. TrustDS compiles human‑readable consent and governance policies into an execution DAG that schedules privacy‑enhancing technologies (PETs) like differential privacy (DP), secure multi‑party computation (SMPC), and trusted execution environments (TEEs) - under explicit latency, utility, and cost budgets. We formalize policy admissibility, prove a safety property for admissible plans, and provide a revocation protocol that bounds consent‑revocation propagation within Δt. A cost‑aware planner co‑optimizes operator placement across edge and cloud to minimize latency while respecting egress restrictions and utility targets. We evaluate TrustDS in four sectors (healthcare, finance, transport, retail) using real‑world topologies, reporting p50/p95/p99 latency, throughput, revocation delay, and utility-privacy trade‑offs with 95% confidence intervals. Against two baselines: centralized transfer and a clean‑room exchange - TrustDS achieves comparable or better utility at lower data exposure, with median end‑to‑end latency improvements of 18–34% and revocation propagation below 120 ms under realistic load. We release a scoring rubric for policy and privacy capabilities that enables repeatable comparison of frameworks. To our knowledge, the explicit composition of policy semantics with PET scheduling and revocation guarantees in an interoperable, multi‑cloud data‑exchange framework is novel and practically useful. data sharing data governance differential privacy federated learning interoperability auditability Full Text Additional Declarations No competing interests reported. Supplementary Files GraphicalAbstractTrustDS.tiff 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-7519920","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":523711874,"identity":"fe7eb487-3819-452b-9eca-0aa27be05f38","order_by":0,"name":"Tirupati Rao 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Validation","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":true,"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":"data sharing, data governance, differential privacy, federated learning, interoperability, 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TrustDS compiles human‑readable consent and governance policies into an execution DAG that schedules privacy‑enhancing technologies (PETs) like differential privacy (DP), secure multi‑party computation (SMPC), and trusted execution environments (TEEs) - under explicit latency, utility, and cost budgets. We formalize policy admissibility, prove a safety property for admissible plans, and provide a revocation protocol that bounds consent‑revocation propagation within Δt. A cost‑aware planner co‑optimizes operator placement across edge and cloud to minimize latency while respecting egress restrictions and utility targets. We evaluate TrustDS in four sectors (healthcare, finance, transport, retail) using real‑world topologies, reporting p50/p95/p99 latency, throughput, revocation delay, and utility-privacy trade‑offs with 95% confidence intervals. Against two baselines: centralized transfer and a clean‑room exchange - TrustDS achieves comparable or better utility at lower data exposure, with median end‑to‑end latency improvements of 18–34% and revocation propagation below 120 ms under realistic load. We release a scoring rubric for policy and privacy capabilities that enables repeatable comparison of frameworks. To our knowledge, the explicit composition of policy semantics with PET scheduling and revocation guarantees in an interoperable, multi‑cloud data‑exchange framework is novel and practically useful.\u003c/p\u003e","manuscriptTitle":"TrustDS: A Policy‑First, Privacy‑Preserving Framework for Interoperable Data Exchange with Real‑World Validation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-03 12:28:56","doi":"10.21203/rs.3.rs-7519920/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"6b89e491-96e1-4507-bfe5-820bb0020e9c","owner":[],"postedDate":"October 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-14T14:39:07+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-03 12:28:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7519920","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7519920","identity":"rs-7519920","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}