A Two-layer Intrusion Detection System based on Fog and Cloud using Improved KNN and MPNN

A Two-layer Intrusion Detection System based on Fog and Cloud using Improved KNN and MPNN | 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 Two-layer Intrusion Detection System based on Fog and Cloud using Improved KNN and MPNN Ali Kaffash, Seyed Reza Kamel, Maryam Kheirabadi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3127041/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 The concept of Internet of Things (IoT) and its countless applications are considered as an inseparable part of modern technology era. The placement of IoT- based devices and their limitations make the environment more vulnerable due to its openness. Security plays a critical role in IoT applications due to pervasiveness of the IoT in all of the aspects in daily life. from the other hand final devices such as their limited computing power, large number of devices connected to each other, and communication between devices and users do not allow for using traditional methods to solve security issues. Intrusion detection systems (IDSs) which can separate malicious traffic from normal mode are among the effective solutions in this field. the installed IDS should be highly accurate and light weight to affect accuracy. In order to bring services closer to electronic devices, a concept called "fog" has emerged. A large number of studies have been conducted to make the light IDS for IoT network utilizing various methods. The present study aims to propose two-layer hierarchical IDS based on machine learning, which detects attacks by considering the limitations of IoT resources. In order to create an efficient and accurate IDS, the combination of two improved K-nearest neighbor (KNN) algorithms and multi-layer perceptron (MLP) neural network applied in the fog and cloud to separate the attacks from normal traffic, respectively. we evaluated our proposed method using IOT23 dataset. The results prove the improvement in accuracy, compared to the previous methods. IoT security intrusion detection system fog cloud KNN MLP 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-3127041","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":215167612,"identity":"03c5cff0-d2bd-48b6-acf0-f1025d1defd8","order_by":0,"name":"Ali Kaffash","email":"","orcid":"","institution":"Islamic Azad University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Kaffash","suffix":""},{"id":215167613,"identity":"4dbb7707-ad23-4a17-be40-a6f840a52f1e","order_by":1,"name":"Seyed Reza Kamel","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYDCCA2wg0kKOgYGH4QBEiLGBGC0SxqRrSWwAaiEO8N0+lvjpRoVE+tr+swcP/GxjkOdvYG77gE+L5Lm0w9I5ZyRyt93ISzjY28ZgOOMAY/MMfFoMzrA3SOe2gbTwGBzgbWNg3MDA2IzXYUAtzb9z/0mkm50/Y3DwbxuDPRFa2I5J5zZIJJgdyDE4DLQlkaAWyTNsadY5xyQMt90AapE5J5E84zABLXxn2Ixv59TYyAMdZvzxTZmNbX97+2O8WtCBBAMDM0kaRsEoGAWjYBRgAwBgdkp1YZLTHwAAAABJRU5ErkJggg==","orcid":"","institution":"Islamic Azad University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Seyed","middleName":"Reza","lastName":"Kamel","suffix":""},{"id":215167614,"identity":"31a103ff-17b4-4833-8562-14a6e2b33d03","order_by":2,"name":"Maryam Kheirabadi","email":"","orcid":"","institution":"Islamic Azad University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Maryam","middleName":"","lastName":"Kheirabadi","suffix":""}],"badges":[],"createdAt":"2023-06-30 06:44:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3127041/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3127041/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":39774513,"identity":"db302a87-e0c9-42d1-978c-79e50ca92a0f","added_by":"auto","created_at":"2023-07-10 08:14:36","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":431661,"visible":true,"origin":"","legend":"","description":"","filename":"FinalVersionAlikaffash.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3127041/v1_covered_8d859a6c-2e0c-4afe-a2b6-72021886918e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Two-layer Intrusion Detection System based on Fog and Cloud using Improved KNN and MPNN","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":"IoT security, intrusion detection system, fog, cloud, KNN, MLP","lastPublishedDoi":"10.21203/rs.3.rs-3127041/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3127041/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe concept of Internet of Things (IoT) and its countless applications are considered as an inseparable part of modern technology era. 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