Secure Cloud Data with Attribute-based Honey Encryption | 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Article Secure Cloud Data with Attribute-based Honey Encryption Reshma Siyal, Jun Long This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4115057/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 Encryption is a Technique to convert plain text into Cipher text, which is unreadable without an appropriate decryption key. Hadoop is a platform to process and store huge amounts of data reliably. It also provides a flexible service for big data through HDFS storage. Inappropriately, Hadoop's lack of built-in security measures makes it more likely that hostile attacks will be made against the data processed or stored using Hadoop. So, the data stored in Hadoop is a big, challenging task. The prevalence of private data attacks underscores the critical need for robust Encryption techniques. In this article, we have used Attribute-based encryption based on Cipher text policy attributes encryption. Attribute-based Honey Encryption (ABHE) is a novel encryption technique that provides an additional layer of security to data stored in a database. This paper especially focused on the file sizes encoded inside the Hadoop. Hadoop is good for handling big data but it lacks security, making data vulnerable to attacks. To fix this, we have created Attribute Honey Encryption (ABHE), a method to encode and decode files securely in HDFS, and compared work with the CP-ABE algorithm and KP-ABE algorithm. ABHE works well even with large files and performs better. This makes Hadoop safer for storing and processing data. Data Security Cloud Storage Security Hadoop Encryption and Decryption (Big data) Privacy protection Access control 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-4115057","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":280665235,"identity":"33bb4278-ad87-4c54-b497-fa0e706d7e46","order_by":0,"name":"Reshma Siyal","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYHACNhDBw8DA3PgAyJCBChClhbHZgIHBgIdoLUDA2CZBlBbz9vZnj27U1MkYHD/YVvGx7Q8PP3tbAsOPim04tcicOWNunHPsMI/BmcS2mzPbDHgke44dYOw5cxunFgmJHDbpHLYDPAYHEttu8wK1GNxIb2BmbMOjRf75M+mcf3U8BucfthUTp0WCwUw6t40ZqDKxjRmiJe0Afi08OUAtfYd5JG88bJaccc4Y5JeEg3j9wn4c6LBvdfZ855MPfvhQJicHDDHDBz8qcGuBA4UDSJwDOBShAvkGopSNglEwCkbBSAQAThVTcnIba7cAAAAASUVORK5CYII=","orcid":"","institution":"CSU","correspondingAuthor":true,"prefix":"","firstName":"Reshma","middleName":"","lastName":"Siyal","suffix":""},{"id":280665236,"identity":"2e3d08f4-9720-41a4-bc45-587114117714","order_by":1,"name":"Jun Long","email":"","orcid":"","institution":"CSU","correspondingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Long","suffix":""}],"badges":[],"createdAt":"2024-03-17 01:44:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4115057/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4115057/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53259054,"identity":"5742033f-917f-43e5-bd95-1aa8bf806045","added_by":"auto","created_at":"2024-03-22 14:13:13","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":825111,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4115057/v1_covered_e17fce6b-43c2-4811-b0ff-95ec7b20c0f2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Secure Cloud Data with Attribute-based Honey Encryption","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":"Data Security, Cloud Storage Security, Hadoop Encryption and Decryption (Big data), Privacy protection, Access control","lastPublishedDoi":"10.21203/rs.3.rs-4115057/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4115057/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEncryption is a Technique to convert plain text into Cipher text, which is unreadable without an appropriate decryption key. Hadoop is a platform to process and store huge amounts of data reliably. It also provides a flexible service for big data through HDFS storage. Inappropriately, Hadoop's lack of built-in security measures makes it more likely that hostile attacks will be made against the data processed or stored using Hadoop. So, the data stored in Hadoop is a big, challenging task. The prevalence of private data attacks underscores the critical need for robust Encryption techniques. In this article, we have used Attribute-based encryption based on Cipher text policy attributes encryption. Attribute-based Honey Encryption (ABHE) is a novel encryption technique that provides an additional layer of security to data stored in a database. This paper especially focused on the file sizes encoded inside the Hadoop. Hadoop is good for handling big data but it lacks security, making data vulnerable to attacks. To fix this, we have created Attribute Honey Encryption (ABHE), a method to encode and decode files securely in HDFS, and compared work with the CP-ABE algorithm and KP-ABE algorithm. ABHE works well even with large files and performs better. This makes Hadoop safer for storing and processing data.\u003c/p\u003e","manuscriptTitle":"Secure Cloud Data with Attribute-based Honey Encryption","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-20 19:31:34","doi":"10.21203/rs.3.rs-4115057/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"ab25d80c-e012-45d8-8163-51825fb05872","owner":[],"postedDate":"March 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-22T14:05:05+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-20 19:31:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4115057","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4115057","identity":"rs-4115057","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}
Text is read by the "Ask this paper" AI Q&A widget below.
Extraction quality varies by source — PMC NXML preserves structure
cleanly, OA-HTML may include some navigation residue, and OA-PDF can
have broken hyphenation. The publisher copy
(via DOI)
is the canonical version.