Intelligent Hybrid Image Encryption Using Adaptive Neural Permutation and Chaotic Key Dynamics

Intelligent Hybrid Image Encryption Using Adaptive Neural Permutation and Chaotic Key Dynamics | 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 Intelligent Hybrid Image Encryption Using Adaptive Neural Permutation and Chaotic Key Dynamics VILAS MAHAJAN, Sridaran Rajagopal This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7836916/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 14 You are reading this latest preprint version Abstract In the era of digital imagery, in critical applications like healthcare, defense and private communication, there is a true need for strong, computationally secure encryption techniques. Traditional cryptographic algorithms, though optimal for text data, are prone to difficulty with images due to high pixel interdependence and data redundancy.. This paper proposes a novel multi-layered image encryption framework that uses Neural Network integrated with multiple chaotic encryptions. It uses a content-adaptive permutation process, facilitated by a deterministic neural network that combined with a diffusion process using chaotic maps. This proposed methodology uses the plaintext sensitivity of the image combined with a user-specified cryptographic key to produce a unique pixel-shuffling permutation, effectively reducing pixel correlation. A chaotic transformation seeded with cryptographically secure keys then manipulates pixel values to produce far-reaching diffusion. This hybrid technique offers good resistance to statistical, differential and brute-force cryptanalysis and is hence a very effective solution for modern-day image security applications. Average test results from 10,224 encrypted images show high entropy = 7.9855, pixel correlation near zero i.e.-0.002 to 0.06, high MSE = 105.505, PSNR = 27.899 dB, low SSIM = 0.00820 and effective immune against differential attacks with NPCR = 99.60% and UACI = 50.0123%. The MAE = 127.453 guarantees strong obscuration making the proposed method highly appropriate for high-security applications. Image Encryption Neural Nets Cryptography Permutation-Diffusion Cybersecurity AI Security Multi-Chaotic Systems Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 25 Mar, 2026 Reviews received at journal 21 Dec, 2025 Reviews received at journal 19 Dec, 2025 Reviews received at journal 08 Dec, 2025 Reviews received at journal 26 Nov, 2025 Reviewers agreed at journal 07 Nov, 2025 Reviewers agreed at journal 05 Nov, 2025 Reviewers agreed at journal 05 Nov, 2025 Reviewers agreed at journal 05 Nov, 2025 Reviewers agreed at journal 05 Nov, 2025 Reviewers invited by journal 05 Nov, 2025 Editor assigned by journal 29 Oct, 2025 Submission checks completed at journal 13 Oct, 2025 First submitted to journal 11 Oct, 2025 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-7836916","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":545523865,"identity":"cf83c4bd-36a0-487d-8ac3-18bce8a259a5","order_by":0,"name":"VILAS 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Dynamics","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":"eurasip-journal-on-information-security","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jins","sideBox":"Learn more about [EURASIP Journal on Information Security](https://jis-eurasipjournals.springeropen.com/)","snPcode":"13635","submissionUrl":"https://submission.nature.com/new-submission/13635/3","title":"EURASIP Journal on Information Security","twitterHandle":"@SpringerEng","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Image Encryption, Neural Nets, Cryptography, Permutation-Diffusion, Cybersecurity, AI Security, Multi-Chaotic Systems","lastPublishedDoi":"10.21203/rs.3.rs-7836916/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7836916/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the era of digital imagery, in critical applications like healthcare, defense and private communication, there is a true need for strong, computationally secure encryption techniques. Traditional cryptographic algorithms, though optimal for text data, are prone to difficulty with images due to high pixel interdependence and data redundancy.. This paper proposes a novel multi-layered image encryption framework that uses Neural Network integrated with multiple chaotic encryptions. It uses a content-adaptive permutation process, facilitated by a deterministic neural network that combined with a diffusion process using chaotic maps. This proposed methodology uses the plaintext sensitivity of the image combined with a user-specified cryptographic key to produce a unique pixel-shuffling permutation, effectively reducing pixel correlation. A chaotic transformation seeded with cryptographically secure keys then manipulates pixel values to produce far-reaching diffusion. This hybrid technique offers good resistance to statistical, differential and brute-force cryptanalysis and is hence a very effective solution for modern-day image security applications. Average test results from 10,224 encrypted images show high entropy\u0026thinsp;=\u0026thinsp;7.9855, pixel correlation near zero i.e.-0.002 to 0.06, high MSE\u0026thinsp;=\u0026thinsp;105.505, PSNR\u0026thinsp;=\u0026thinsp;27.899 dB, low SSIM\u0026thinsp;=\u0026thinsp;0.00820 and effective immune against differential attacks with NPCR\u0026thinsp;=\u0026thinsp;99.60% and UACI\u0026thinsp;=\u0026thinsp;50.0123%. The MAE\u0026thinsp;=\u0026thinsp;127.453 guarantees strong obscuration making the proposed method highly appropriate for high-security applications.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e","manuscriptTitle":"Intelligent Hybrid Image Encryption Using Adaptive Neural Permutation and Chaotic Key Dynamics","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-17 09:37:58","doi":"10.21203/rs.3.rs-7836916/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-25T11:02:57+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-21T17:42:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-19T10:06:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-09T03:47:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-26T15:38:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"316756485912024123600446206883234390130","date":"2025-11-07T07:06:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"31016038374856980162521715248064050690","date":"2025-11-06T01:49:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"72055297307976875540653530563614943509","date":"2025-11-05T12:48:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"291860591704741414606427316397873734011","date":"2025-11-05T12:42:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"46556831105593412232494470681818835731","date":"2025-11-05T12:40:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-05T12:34:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-29T14:26:32+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-13T10:43:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"EURASIP Journal on Information Security","date":"2025-10-11T18:05:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"eurasip-journal-on-information-security","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jins","sideBox":"Learn more about [EURASIP Journal on Information Security](https://jis-eurasipjournals.springeropen.com/)","snPcode":"13635","submissionUrl":"https://submission.nature.com/new-submission/13635/3","title":"EURASIP Journal on Information Security","twitterHandle":"@SpringerEng","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0c32b09f-e958-44e5-90f2-2431fcaa2611","owner":[],"postedDate":"November 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T15:06:41+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-17 09:37:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7836916","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7836916","identity":"rs-7836916","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}