High-Precision Detection of DDoS Attacks in Power Communication Networks Based on a Composite Sin-Cos Bee Colony Algorithm

High-Precision Detection of DDoS Attacks in Power Communication Networks Based on a Composite Sin-Cos Bee Colony Algorithm | 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 High-Precision Detection of DDoS Attacks in Power Communication Networks Based on a Composite Sin-Cos Bee Colony Algorithm Fajia Ji, Lei Wang, Zhaohe Wang, Yan Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9312698/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract With the increasing complexity of power communication networks, Distributed Denial of Service (DDoS) attacks have become a major threat to system stability. This paper proposes a DDoS detection method based on a composite Sin-Cos bee colony algorithm. The method integrates the advantages of the Artificial Bee Colony (ABC) algorithm and the Sin-Cos algorithm to optimize feature extraction and clustering analysis, thereby constructing an adaptive attack signal model. Experimental results on the CIC-DDoS2019 dataset demonstrate that the proposed method achieves a detection accuracy of 99.93%, with precision, recall, and F1-score all exceeding 99.9%. Moreover, the training time is only 16.36 seconds, which is comparable to that of the traditional bee colony algorithm. Compared with particle swarm and conventional bee colony methods, the proposed approach exhibits stronger robustness and generalization ability in detecting unknown attacks. These findings confirm that the method can provide an efficient and reliable security solution for power communication systems. Improved bee colony algorithm Computer network DDOS attack Combination optimization Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 16 May, 2026 Reviews received at journal 12 May, 2026 Reviewers agreed at journal 10 May, 2026 Reviewers invited by journal 30 Apr, 2026 Editor invited by journal 19 Apr, 2026 Editor assigned by journal 06 Apr, 2026 Submission checks completed at journal 06 Apr, 2026 First submitted to journal 03 Apr, 2026 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. 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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-9312698","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":632133945,"identity":"7528be26-7fc8-41c9-a2a0-0801d3347d3e","order_by":0,"name":"Fajia Ji","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIie2RoQrCUBSGz8pWDqweQQXfwDGYhoGvcoawtKBtSQaCloHVxxgI5isXtewBFmc3aDMYvGKy3C0K3q8d+D/4fw6AwfCDTASwgJD67vuqAYaNikooBcnvZGBl3FJRIESFaK044iIeOI5253xUcxr64Mhjod2CzIdcFduXpZdxGQeAcVzpizELROrtq8TLopUMgTDQK27NhyeStdu2VohZYk6Dgj5K0EKpWXYr8qk8zbdqi283bnGT6f06W/Td9bK43dLQ2zjypFXUT/j7tvXxN45ozhgMBsN/8wLFIky/0eH/rgAAAABJRU5ErkJggg==","orcid":"","institution":"State Grid Henan Electric Power Company Information and Communication Branch","correspondingAuthor":true,"prefix":"","firstName":"Fajia","middleName":"","lastName":"Ji","suffix":""},{"id":632133946,"identity":"b2cc6e08-4791-4095-8fa7-94c9fa8ad673","order_by":1,"name":"Lei Wang","email":"","orcid":"","institution":"State Grid Henan Electric Power Company Information and Communication Branch","correspondingAuthor":false,"prefix":"","firstName":"Lei","middleName":"","lastName":"Wang","suffix":""},{"id":632133947,"identity":"7ea5be7f-abd0-4e99-b0c0-a4e118aa639d","order_by":2,"name":"Zhaohe Wang","email":"","orcid":"","institution":"State Grid Henan Electric Power Company Information and Communication Branch","correspondingAuthor":false,"prefix":"","firstName":"Zhaohe","middleName":"","lastName":"Wang","suffix":""},{"id":632133948,"identity":"a9fda08b-ef6c-4f87-a1c4-40366a92db08","order_by":3,"name":"Yan Liu","email":"","orcid":"","institution":"State Grid Henan Electric Power Company Information and Communication Branch","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2026-04-03 12:08:52","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9312698/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9312698/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108806516,"identity":"7f3d4914-43fe-43d4-af5e-f67303fc2da1","added_by":"auto","created_at":"2026-05-08 15:28:48","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":566112,"visible":true,"origin":"","legend":"","description":"","filename":"paper.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9312698/v1_covered_6bbdabbb-e375-4e37-a60f-d9d56d72bc8d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"High-Precision Detection of DDoS Attacks in Power Communication Networks Based on a Composite Sin-Cos Bee Colony Algorithm","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":"discover-applied-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Applied Sciences](https://link.springer.com/journal/42452)","snPcode":"42452","submissionUrl":"https://submission.springernature.com/new-submission/42452/3","title":"Discover Applied Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Improved bee colony algorithm, Computer network, DDOS attack, Combination optimization","lastPublishedDoi":"10.21203/rs.3.rs-9312698/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9312698/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWith the increasing complexity of power communication networks, Distributed Denial of Service (DDoS) attacks have become a major threat to system stability. 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