CRS:A Website Fingerprinting Technique for Dark Web Tor Traffic

CRS:A Website Fingerprinting Technique for Dark Web Tor Traffic | 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 CRS:A Website Fingerprinting Technique for Dark Web Tor Traffic Dawei Xu, Jiaxin Zhang, Fan Huang, Yilin Chen, Baokun Zheng This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6169549/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 12 You are reading this latest preprint version Abstract With the development of internet and communication technologies, life has become more convenient, but privacy and security issues have emerged as a consequence. While the Tor network protects privacy, it is often used for illegal activities due to its anonymity features, posing a threat to societal security. In Tor network traffic identification, traditional methods face challenges in feature extraction and model degradation. To address these issues, this study proposes a website fingerprinting model for Tor traffic, named CRS. The model mitigates the degradation problem of deep networks through skip connections and enhances the accuracy and flexibility of feature extraction via adaptive similarity calculation. Evaluation results show that the CRS model achieves an identification accuracy of over 98% for undefended traffic in closed environments; 91.32% under WTF-PAD defense, and 49.7% under Walkie-Talkie defense. In open environments, the precision and recall for undefended traffic both reach 98%; under WTF-PAD defense, precision is 90%, and recall is 94%. Even under both WTF-PAD and Walkie-Talkie defenses, the CRS model’s precision and recall remain significantly higher than those of other comparison models. These results validate the superior performance of the CRS model, highlight the importance of effectively addressing various defense mechanisms, and provide new insights for dark web traffic analysis and network security defense, with significant theoretical and practical value. Tor Website Fingerprinting Deep Learning Adaptive feature extraction Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 11 May, 2025 Reviews received at journal 11 May, 2025 Reviewers agreed at journal 05 May, 2025 Reviewers agreed at journal 01 May, 2025 Reviews received at journal 30 Apr, 2025 Reviewers agreed at journal 30 Apr, 2025 Reviewers agreed at journal 29 Apr, 2025 Reviewers agreed at journal 29 Apr, 2025 Reviewers invited by journal 29 Apr, 2025 Editor assigned by journal 29 Mar, 2025 Submission checks completed at journal 06 Mar, 2025 First submitted to journal 06 Mar, 2025 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. 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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-6169549","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":425084317,"identity":"f3c613a7-aaf7-4081-b89e-533598bfe93c","order_by":0,"name":"Dawei Xu","email":"","orcid":"","institution":"Changchun University","correspondingAuthor":false,"prefix":"","firstName":"Dawei","middleName":"","lastName":"Xu","suffix":""},{"id":425084318,"identity":"2c232814-3331-4250-98fb-20035a53734f","order_by":1,"name":"Jiaxin Zhang","email":"","orcid":"","institution":"Changchun University","correspondingAuthor":false,"prefix":"","firstName":"Jiaxin","middleName":"","lastName":"Zhang","suffix":""},{"id":425084321,"identity":"f1b87280-af35-4b77-adad-2135599ea1d7","order_by":2,"name":"Fan Huang","email":"","orcid":"","institution":"Changchun University","correspondingAuthor":false,"prefix":"","firstName":"Fan","middleName":"","lastName":"Huang","suffix":""},{"id":425084329,"identity":"665806e8-a81c-4a8e-99de-38f04420ed80","order_by":3,"name":"Yilin Chen","email":"","orcid":"","institution":"Changchun University","correspondingAuthor":false,"prefix":"","firstName":"Yilin","middleName":"","lastName":"Chen","suffix":""},{"id":425084332,"identity":"da86bc64-5fdf-458e-ad2a-12668e2205af","order_by":4,"name":"Baokun Zheng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYDACCSBmbEiQA1EHGBiYiddiDGKTpiWxgWgt8rObjz38uiMtvX9G7oEDDBXWiQ3sZw/g1cI451i6seyZnNwZN/ISDjCcSU9s4MlLwKuFWSLHTFqyrSJ3g0SOwQHGtsOJDRI8Bni1sEnkfwNpSTcAa/lHhBYeiRw2yY9tOQkQLQ1EaJGQSDOTZjyTZjjjzLuEAwlAj7Xx5ODXIj8j+Znkzx3J8vztuQcffKixlu1nP4NfCwgw80DcyMCQAPIdQfVAwPgDpmUUjIJRMApGATYAAHoARekQAG11AAAAAElFTkSuQmCC","orcid":"","institution":"China University of Political Science and Law","correspondingAuthor":true,"prefix":"","firstName":"Baokun","middleName":"","lastName":"Zheng","suffix":""}],"badges":[],"createdAt":"2025-03-06 10:23:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6169549/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6169549/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78136552,"identity":"62bb6b10-8642-4c1a-8d2e-dbf1e8632592","added_by":"auto","created_at":"2025-03-10 09:26:43","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":712522,"visible":true,"origin":"","legend":"","description":"","filename":"CRSAWebsiteFingerprintingTechniqueforDarkWebTorTraffic.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6169549/v1_covered_512625a8-338b-4951-ad76-c4c5f38f1f66.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"CRS:A Website Fingerprinting Technique for Dark Web Tor Traffic","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":"peer-to-peer-networking-and-applications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ppna","sideBox":"Learn more about [Peer-to-Peer Networking and Applications](http://link.springer.com/journal/12083)","snPcode":"12083","submissionUrl":"https://submission.nature.com/new-submission/12083/3","title":"Peer-to-Peer Networking and Applications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Tor, Website Fingerprinting, Deep Learning, Adaptive feature extraction","lastPublishedDoi":"10.21203/rs.3.rs-6169549/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6169549/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"With the development of internet and communication technologies, life has become more convenient, but privacy and security issues have emerged as a consequence. 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