Robust Secure Aggregation For Co-located IoT Devices With Corruption Localization

Robust Secure Aggregation For Co-located IoT Devices With Corruption Localization | 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 Robust Secure Aggregation For Co-located IoT Devices With Corruption Localization Giovanni Di Crescenzo, Elina van Kempen, Gene Tsudik This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6762696/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 Many Internet-of-Things (IoT) applications benefit from secure Federated (Machine) Learning (FL) techniques, e.g., industrial automation and smart cities. Since IoT devices have limited resources, such techniques need to be very efficient. In this paper, we propose a formal model as well as a new means for provably secure and efficient (i.e., IoT-friendly) aggregation for FL in IoT settings. Besides input privacy, it offers result correctness and malicious input localization, both robust against up to a threshold of malicious devices. The proposed techniques involve no interaction among devices, which only send a short message, and perform lightweight encryption and integrity detection. Secure aggregation IoT Federated learning Co-location 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-6762696","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":467641460,"identity":"c6a507f5-96c4-4ce8-86e3-51edebb65766","order_by":0,"name":"Giovanni Di Crescenzo","email":"","orcid":"","institution":"Peraton (United States)","correspondingAuthor":false,"prefix":"","firstName":"Giovanni","middleName":"Di","lastName":"Crescenzo","suffix":""},{"id":467641461,"identity":"4db11c8c-7131-4686-9c81-f0e258445940","order_by":1,"name":"Elina van Kempen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwUlEQVRIiWNgGAWjYJACxgYgwQ/EBxgYmEnQItlAshaDA2A2EVr4JZKfPZxRsS3P+EbywwMMFdaJDYS0SM5IMzfccOZ2sdmNNKBFZ9IJazE4c8BM8mHb7cRtN3IYDjC2HSasxf7M8W+SD//dTtw8A6TlHxFaDNh7zCQ3NtxO3CAB0tJAhBaJ4z1lkjOO3S6WOPPM4EDCsXRjglr4m9m3SfbU3M7jb09+/OFDjbUsQS0wkIBEkqRlFIyCUTAKRgE2AABe8kZYfNTkTQAAAABJRU5ErkJggg==","orcid":"","institution":"University of California, Irvine","correspondingAuthor":true,"prefix":"","firstName":"Elina","middleName":"van","lastName":"Kempen","suffix":""},{"id":467641462,"identity":"77f50ca2-1636-4bad-85f5-87aef86b7785","order_by":2,"name":"Gene Tsudik","email":"","orcid":"","institution":"University of California, Irvine","correspondingAuthor":false,"prefix":"","firstName":"Gene","middleName":"","lastName":"Tsudik","suffix":""}],"badges":[],"createdAt":"2025-05-27 22:08:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6762696/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6762696/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107145402,"identity":"e977248f-d68b-43fc-8035-f7e0799641ab","added_by":"auto","created_at":"2026-04-17 09:42:57","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":548290,"visible":true,"origin":"","legend":"","description":"","filename":"paper.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6762696/v1_covered_54c77d22-287a-4b1d-80ff-4abd546f8da1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Robust Secure Aggregation For Co-located IoT Devices With Corruption Localization","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":"Secure aggregation, IoT, Federated learning, Co-location","lastPublishedDoi":"10.21203/rs.3.rs-6762696/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6762696/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Many Internet-of-Things (IoT) applications benefit from secure Federated (Machine) Learning (FL) techniques, e.g., industrial automation and smart cities. 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