A Secure data-driven algorithm against malicious intrusion signals in mobile communication networks

A Secure data-driven algorithm against malicious intrusion signals in mobile communication networks | 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 A Secure data-driven algorithm against malicious intrusion signals in mobile communication networks Yongfei Yu, Mohamed Baza, Amar Rasheed This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5310069/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Mar, 2025 Read the published version in Mobile Networks and Applications → Version 1 posted You are reading this latest preprint version Abstract Intrusion signals in mobile communication networks are often disguised as normal communication signals to attack, which is highly covert. This makes it difficult to be accurately recognized and increases the danger of data leakage. For this reason, this paper proposes a full link security defense algorithm against malicious intrusion signals in mobile communication networks based on data-driven technique. This algorithm uses the support vector machine technology to construct an identification model against the malicious intrusion signal of the full link and introduces the firefly algorithm to optimize the support vector parameters of the model to ensure the accuracy of the model in identifying the malicious intrusion signal. In addition, this algorithm uses a network full link security defense model based on dynamic camouflage technology to dynamically simulate any element of the full link in the mobile communication network, and at the same time constructs heterogeneous executives to distribute the results of the malicious intrusion signal to each selected heterogeneous executor. Experimental results show that the proposed algorithm can accurately identify different types of malicious intrusion type signal samples, so that the interception rate of the intrusion defense system against malicious intrusion signals is greater than 99%, and the important data loss rate is less than 1%. data-driven mobile communication networks malicious intrusion signals full link security defense dynamic camouflage technology Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 26 Mar, 2025 Read the published version in Mobile Networks and Applications → 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. 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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-5310069","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":373548477,"identity":"c2ce93d3-6fd9-4f78-be22-6395497aab9f","order_by":0,"name":"Yongfei Yu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYPACOQY29gYo+wBxWowZ2HgOMDaQpoVBIoFILQY3cgwfF/wykOOTfGP+4EcNgxzfjQTGzwX4tRgbz+wzMGaTzjFs7DnGYCx5I4FZegZ+LWbSvD1/EtuAWpqBTkvccCOBjZmHsBaD+jbJM2At9cRp4flhkMAmwQPWkmBASIvkmWfFxrwNBoZtPGmFM3uOSRjOPPOwWRqfFr7jyRsf8/wxkJdvP7zhw48aG3mgyMHP+LQoHOAwYGBsAzGBDGDsADE0fnAB+Qb2BwwMf0BMEGMUjIJRMApGARYAACo7S0QZhDw1AAAAAElFTkSuQmCC","orcid":"","institution":"Yantai City College of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Yongfei","middleName":"","lastName":"Yu","suffix":""},{"id":373548478,"identity":"a282bce3-c6ef-44a3-8580-8313a0823d2a","order_by":1,"name":"Mohamed Baza","email":"","orcid":"","institution":"College of Charleston","correspondingAuthor":false,"prefix":"","firstName":"Mohamed","middleName":"","lastName":"Baza","suffix":""},{"id":373548480,"identity":"457b1b0c-b2f9-4f04-95f8-1e7227964705","order_by":2,"name":"Amar Rasheed","email":"","orcid":"","institution":"Sam Houston State University","correspondingAuthor":false,"prefix":"","firstName":"Amar","middleName":"","lastName":"Rasheed","suffix":""}],"badges":[],"createdAt":"2024-10-22 08:53:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5310069/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5310069/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11036-025-02446-9","type":"published","date":"2025-03-26T15:57:33+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79604881,"identity":"9e5b44c8-220c-4b12-80ab-43d4402815f2","added_by":"auto","created_at":"2025-03-31 16:08:12","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":402877,"visible":true,"origin":"","legend":"","description":"","filename":"finalyuyongfei1022.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5310069/v1_covered_0c0094d0-4e77-4ce9-afb9-b80c5c82b6a5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Secure data-driven algorithm against malicious intrusion signals in mobile communication networks","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":true,"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":"data-driven, mobile communication networks, malicious intrusion signals, full link, security defense, dynamic camouflage technology","lastPublishedDoi":"10.21203/rs.3.rs-5310069/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5310069/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIntrusion signals in mobile communication networks are often disguised as normal communication signals to attack, which is highly covert. This makes it difficult to be accurately recognized and increases the danger of data leakage. For this reason, this paper proposes a full link security defense algorithm against malicious intrusion signals in mobile communication networks based on data-driven technique. This algorithm uses the support vector machine technology to construct an identification model against the malicious intrusion signal of the full link and introduces the firefly algorithm to optimize the support vector parameters of the model to ensure the accuracy of the model in identifying the malicious intrusion signal. In addition, this algorithm uses a network full link security defense model based on dynamic camouflage technology to dynamically simulate any element of the full link in the mobile communication network, and at the same time constructs heterogeneous executives to distribute the results of the malicious intrusion signal to each selected heterogeneous executor. 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