MFDI: Securing IIoT: An Investigation intoMachine Learning-Based False Data Injection Attacks

MFDI: Securing IIoT: An Investigation intoMachine Learning-Based False Data Injection Attacks | 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 MFDI: Securing IIoT: An Investigation intoMachine Learning-Based False Data Injection Attacks Kumar Saurabh Kumar Saurabh, Ashwani Kumar Sharma Ashwani Kumar Sharma, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5890609/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 Now a days, Industries like manufacturing, power generation, and smart transportation are using advanced internet-connected systems. Unfortunately, this makes them more vulnerable to cyberattacks. To protect against these attacks, policymakers have created rules, implemented security features like secure login and encryption to safeguard these systems. However, the increasing number of cyberattacks like SQL injection attacks, False data Injection attacks, Phishing, etc. shows that these measures are not enough, and have some limitations. The false data injection attack is one of the most accruing attacks possible on Physical and cyber layers both. In Ukraine, there is a total blackout due to false data injection attacks, such case study of FDI attacks in power systems shows the severity of false data injection attacks. In this FDI attack, machines show wrong readings which might lead to economic and life loss, as critical infrastructures like hospitals, smart grids, modern transportation systems, etc. are fully dependent on electricity. In this paper, a few best-performing Machine learning algorithms have been implemented and after Exploratory Data Analysis and Data Preprocessing steps, GridSearchCv is used for hyperparameter tuning, which makes our proposed model outperformer than previous works in FDI attack detection. To evaluate the proposed model’s reliability, the performance evaluation is also done on Power System Attack Datasets provided by Mississippi State University and Oak Ridge National Laboratory. The Decision Tree algorithm stands out as the top performer with a training accuracy of 100% and a testing accuracy of 98%. the other performance metrics like Recall, F1 score, sensitivity training, and testing time also scored well in terms of comparison with other algorithms. False Data Injection Attack Machine Learning Industrial Internet Of Thing(IIot) 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. 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-5890609","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":407681222,"identity":"cd3d15e4-f26c-4a7a-96ef-9bba74e9f095","order_by":0,"name":"Kumar Saurabh Kumar Saurabh","email":"","orcid":"","institution":"Indian Institute of Information Technology, Allahabad","correspondingAuthor":false,"prefix":"","firstName":"Kumar","middleName":"Saurabh Kumar","lastName":"Saurabh","suffix":""},{"id":407681223,"identity":"1e68fd3d-437f-4540-bf71-7804f0248d2d","order_by":1,"name":"Ashwani Kumar Sharma Ashwani Kumar Sharma","email":"","orcid":"","institution":"Sardar Vallabhbhai National Institute of Technology Surat","correspondingAuthor":false,"prefix":"","firstName":"Ashwani","middleName":"Kumar Sharma Ashwani Kumar","lastName":"Sharma","suffix":""},{"id":407681224,"identity":"6a80d0e6-e503-48ef-9498-82fea9b48d0d","order_by":2,"name":"Supriya Mishra Supriya Mishra","email":"","orcid":"","institution":"Sardar Vallabhbhai National Institute of Technology Surat","correspondingAuthor":false,"prefix":"","firstName":"Supriya","middleName":"Mishra Supriya","lastName":"Mishra","suffix":""},{"id":407681225,"identity":"94f8841a-896f-435b-837e-ff83949ed7fc","order_by":3,"name":"Alok Kumar Alok Kumar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYDACdgZmxgYwA0QWMDBIENTCDNPCc4CB4YABSVokEojUwt/MfNhwZts2efOZj49JfzCwkZNsYH746AYeLRKH2ZITN7bdNpxzOy1N4oBBmrE0A5uxcQ4+aw7zGB982HabcYZ0jhlQy+HEeQw8bNL4tMhDtdjPkDxDpBYDoBaQwxJnSPBAtMwmpMUQ6BfDGeduJ8/gSUu2OAP0i2QzAb/IHW8+LNlTdtt2BvvhgzcqKmzkJI43P3yM1/uYgJk05aNgFIyCUTAKsAAANCRJJdWFwOIAAAAASUVORK5CYII=","orcid":"","institution":"Sir Padampat Singhania University","correspondingAuthor":true,"prefix":"","firstName":"Alok","middleName":"Kumar Alok","lastName":"Kumar","suffix":""}],"badges":[],"createdAt":"2025-01-23 19:08:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5890609/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5890609/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":76375138,"identity":"e826a66e-2835-4927-a0ce-5291f2027118","added_by":"auto","created_at":"2025-02-15 22:46:24","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":924043,"visible":true,"origin":"","legend":"","description":"","filename":"SpringerMFDI.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5890609/v1_covered_216b94be-07da-41e8-bc16-c1eb05defa33.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"MFDI: Securing IIoT: An Investigation intoMachine Learning-Based False Data Injection Attacks","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":"False Data Injection Attack, Machine Learning, Industrial Internet Of Thing(IIot)","lastPublishedDoi":"10.21203/rs.3.rs-5890609/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5890609/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNow a days, Industries like manufacturing, power generation, and smart transportation are using advanced internet-connected systems. 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