S-AI-Cyber : A Symbolic Hormonal Architecture for Adaptive and Parsimonious Cybersecurity

S-AI-Cyber : A Symbolic Hormonal Architecture for Adaptive and Parsimonious Cybersecurity | 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 S-AI-Cyber : A Symbolic Hormonal Architecture for Adaptive and Parsimonious Cybersecurity said slaoui This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7279427/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 This article introduces S-AI-Cyber, a novel cyber defense architecture based on symbolic hormonal orchestration and parsimonious agent activation. Inspired by endocrine signaling mechanisms, the system replaces traditional threshold-based or black-box AI models with a biologically grounded framework combining transparency, adaptability, and computational frugality. S-AI-Cyber relies on five interacting components : Gland Agents emit symbolic hormones in response to perceived threats; the HormonalEngine modulates signal propagation and decay; Specialized Agents perform detection, classification, response, and inhibition; a Cyber-MetaAgent coordinates agent selection based on hormonal profiles; and a MemoryAgent ensures contextual traceability. All decisions are made through symbolic propagation without predefined rule sets or opaque inference. The proposed system was validated through two simulated asymmetric cyberattack scenarios : a Slow Port Scan (low-frequency stealth reconnaissance) and a Fast DDoS Attack (volumetric flooding). Each scenario was evaluated over multiple time steps, tracking hormonal levels, agent activation, and response strategies. The results demonstrate that S-AI-Cyber activates agents only when necessary, with distinct hormonal signatures for low- and high-risk threats. The system displays both reactive efficiency and symbolic explainability, while ensuring minimal resource usage during benign phases. The article provides full pseudocode, Python implementation excerpts, and symbolic execution traces for reproducibility. The findings support the viability of symbolic hormonal modulation as a foundation for next-generation, explainable, and context-aware cybersecurity systems, particularly in edge, IoT, and resource-constrained environments. Artificial Intelligence and Machine Learning Symbolic Artificial Intelligence Hormonal Orchestration Parsimonious Activation Bio-Inspired Cybersecurity Adaptive Agent Systems Explainable AI Cyberattack Response Multi-Agent Coordination Hormonal Signaling Edge and IoT Security Full Text Additional Declarations The authors declare no competing interests. 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-7279427","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":494738664,"identity":"4d881c92-7838-44e5-805c-aa5be249d78d","order_by":0,"name":"said slaoui","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYHACxgNAgoefgYH9A9F6wFokGxjYiLcGpIXB4ACxWuQb2B8c+FFxWMb4Rnba4woGO3kGscMP8GoxOMBjcLDnzGEesxu52w3PMCQbNkinGeDXwsDDcIC3DaxlA9A/zAkM0gn4tYAcdvAvUIvxDLCWeqCWdAIhd4DB4DDIFgOJ3G1ALYeBWnIIOAyo+LDMmXQeiTNvNxs2GBw3bJPOKcDvsPb2hw/fVFjb87fnbnzYUFEtzy+dvgG/w5hRLWUgJUJHwSgYBaNgFOACABX1QgIXA026AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0009-0001-6900-8102","institution":"Mohammed V university","correspondingAuthor":true,"prefix":"","firstName":"said","middleName":"","lastName":"slaoui","suffix":""}],"badges":[],"createdAt":"2025-08-02 16:22:22","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7279427/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7279427/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88317575,"identity":"bba747c6-6a2d-4f14-bed0-3edeb23f7327","added_by":"auto","created_at":"2025-08-05 08:20:23","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":768578,"visible":true,"origin":"","legend":"","description":"","filename":"SlaouiSAICYBERV2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7279427/v1_covered_884304ab-0e1b-401a-ba89-4feaac89dd9f.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eS-AI-Cyber : A Symbolic Hormonal Architecture for Adaptive and Parsimonious Cybersecurity\u003c/strong\u003e\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Mohammed V University","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":"Symbolic Artificial Intelligence, Hormonal Orchestration, Parsimonious Activation, Bio-Inspired Cybersecurity, Adaptive Agent Systems, Explainable AI, Cyberattack Response, Multi-Agent Coordination, Hormonal Signaling, Edge and IoT Security","lastPublishedDoi":"10.21203/rs.3.rs-7279427/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7279427/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis article introduces S-AI-Cyber, a novel cyber defense architecture based on symbolic hormonal orchestration and parsimonious agent activation. Inspired by endocrine signaling mechanisms, the system replaces traditional threshold-based or black-box AI models with a biologically grounded framework combining transparency, adaptability, and computational frugality.\u003c/p\u003e\u003cp\u003eS-AI-Cyber relies on five interacting components : Gland Agents emit symbolic hormones in response to perceived threats; the HormonalEngine modulates signal propagation and decay; Specialized Agents perform detection, classification, response, and inhibition; a Cyber-MetaAgent coordinates agent selection based on hormonal profiles; and a MemoryAgent ensures contextual traceability. All decisions are made through symbolic propagation without predefined rule sets or opaque inference.\u003c/p\u003e\u003cp\u003eThe proposed system was validated through two simulated asymmetric cyberattack scenarios : a Slow Port Scan (low-frequency stealth reconnaissance) and a Fast DDoS Attack (volumetric flooding). Each scenario was evaluated over multiple time steps, tracking hormonal levels, agent activation, and response strategies. The results demonstrate that S-AI-Cyber activates agents only when necessary, with distinct hormonal signatures for low- and high-risk threats. The system displays both reactive efficiency and symbolic explainability, while ensuring minimal resource usage during benign phases.\u003c/p\u003e\u003cp\u003eThe article provides full pseudocode, Python implementation excerpts, and symbolic execution traces for reproducibility. 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