Unveiling potential threats: backdoor attacks in single-cell pretrained models

Unveiling potential threats: backdoor attacks in single-cell pretrained models | 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 Brief Communication Unveiling potential threats: backdoor attacks in single-cell pretrained models Shengquan Chen, Sicheng Feng, Siyu Li, Luonan Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4653577/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 Single-cell pretrained models, despite their superior performance, face significant yet often overlooked threats from backdoor attacks. Here we propose a straightforward backdoor strategy to demonstrate the vulnerabilities of these models, achieving high attack success rates while maintaining clean accuracy. We also suggest five potential defense strategies to mitigate these threats. Our findings underscore the imperative for the biomedical community to adopt robust defense mechanisms to safeguard research integrity and reliability. Biological sciences/Computational biology and bioinformatics/Machine learning Biological sciences/Computational biology and bioinformatics/Computational models Full Text Additional Declarations There is NO Competing Interest. 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-4653577","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Brief Communication","associatedPublications":[],"authors":[{"id":326030818,"identity":"5320dd83-e715-4bc5-9bb5-a20e5f174684","order_by":0,"name":"Shengquan Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCUlEQVRIiWNgGAWjYDACCQSTDYgt5ECsAw9I0CJhDNaSQIqWxAYQE58W+dnNxx5+KTssb87A/OzBxx0S6fPDDj8E2mInp9uAXYvBnWPpxjLnDhvubGAzN5x5RiJ34+00A6CWZGOzAzi0SOSYSUu2HWbccICHTZq3DahldgJIy4HEbTi0yM/I/wbSYg/W8rdNIt1wdvoHvFoYbuSwSX5sO5wI1sLYJpEgL52D3xaDG2lm0gzn0pM3HGYzk+xtkzDcIJ1TcCDBALdf5GckP5P8UWZtu+F48zOJn2028vKz0zd/+FBhJ4dLCwgw84BihBlmL1ilAW7lIMD4gw3Z3gb8qkfBKBgFo2DkAQCd018jWR6pDgAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-3503-9306","institution":"Nankai University","correspondingAuthor":true,"prefix":"","firstName":"Shengquan","middleName":"","lastName":"Chen","suffix":""},{"id":326030819,"identity":"0cb7ae5f-7bb2-4093-977a-8e8e670f8ed4","order_by":1,"name":"Sicheng Feng","email":"","orcid":"","institution":"Nankai University","correspondingAuthor":false,"prefix":"","firstName":"Sicheng","middleName":"","lastName":"Feng","suffix":""},{"id":326030820,"identity":"432c6ddb-bd62-4945-8445-b46c347578cb","order_by":2,"name":"Siyu Li","email":"","orcid":"","institution":"Nankai University","correspondingAuthor":false,"prefix":"","firstName":"Siyu","middleName":"","lastName":"Li","suffix":""},{"id":326030821,"identity":"8227ca00-b2e3-4aae-a93e-b2945898c6fd","order_by":3,"name":"Luonan Chen","email":"","orcid":"https://orcid.org/0000-0002-3960-0068","institution":"Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science.Chinese Academy of Science","correspondingAuthor":false,"prefix":"","firstName":"Luonan","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2024-06-28 09:15:52","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4653577/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4653577/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":61053551,"identity":"4753b70e-cfc9-4c21-b884-2822aac326c7","added_by":"auto","created_at":"2024-07-25 04:59:24","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2682384,"visible":true,"origin":"","legend":"Article File","description":"","filename":"manuscriptscBackdoor.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4653577/v1_covered_0d5fda88-4f45-4b1b-875d-1e5c8072855c.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Unveiling potential threats: backdoor attacks in single-cell pretrained models","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":"","lastPublishedDoi":"10.21203/rs.3.rs-4653577/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4653577/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Single-cell pretrained models, despite their superior performance, face significant yet often overlooked threats from backdoor attacks. 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