A Reconfigured RLWE-Based Mutual Authentication Protocol for Post- Quantum IoT Security | 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 Reconfigured RLWE-Based Mutual Authentication Protocol for Post- Quantum IoT Security S. Catherin Sonia, T Jaya This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9252526/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 31 You are reading this latest preprint version Abstract The conventional cryptographic algorithm faces a threat due to the evolution of quantum computing algorithms. In recent days, IoT devices demand authentication techniques to ensure a perfectly secure system. Thus, to address this issue, this paper presents a Modified Ring Learning with Errors–based Mutual Authentication (MRMA) scheme tailored for resource-constrained IoT environments. The computational hardness of the RLWE problem, the proposed scheme employs polynomial-level optimizations to reduce key size and computational overhead, also preserving post-quantum security in IoT devices. To further enhance the security–efficiency trade-off, a Quantum Approximate Optimization Algorithm (QAOA) driven parameter tuning layer is introduced, formulating cryptographic parameter selection as a concern for a multi-objective optimization problem over polynomial degree, modulus, and noise distribution. Also, to improve latency and throughput, the assistance of QAOA is needed. The traditional scheme requires larger keys (512–2048 bits) and high processing time. Our performance analysis proves that the proposed MRMA scheme implements a compact 256-bit key, includes a low authentication latency of 0.0065 seconds, a throughput of 900 operations per second, and an Authentication Acceptance Rate (AAR) of 99.2%. The results prove that the performance is better than typical RLWE- and MLWE-based IoT authentication schemes. Thus, the proposed MRMA scheme supports a secure, lightweight authentication framework, making it suitable for IoT and post-quantum applications. Post-Quantum Cryptography Ring Learning With Errors Mutual Authentication Internet of Things Security Lattice-Based Cryptography Cryptographic Attacks Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 17 Apr, 2026 Reviews received at journal 16 Apr, 2026 Reviews received at journal 11 Apr, 2026 Reviews received at journal 11 Apr, 2026 Reviews received at journal 09 Apr, 2026 Reviews received at journal 06 Apr, 2026 Reviewers agreed at journal 06 Apr, 2026 Reviews received at journal 06 Apr, 2026 Reviews received at journal 05 Apr, 2026 Reviews received at journal 05 Apr, 2026 Reviewers agreed at journal 04 Apr, 2026 Reviewers agreed at journal 03 Apr, 2026 Reviewers agreed at journal 03 Apr, 2026 Reviews received at journal 03 Apr, 2026 Reviews received at journal 03 Apr, 2026 Reviewers agreed at journal 03 Apr, 2026 Reviews received at journal 02 Apr, 2026 Reviewers agreed at journal 02 Apr, 2026 Reviewers agreed at journal 02 Apr, 2026 Reviewers agreed at journal 02 Apr, 2026 Reviewers agreed at journal 01 Apr, 2026 Reviews received at journal 01 Apr, 2026 Reviews received at journal 01 Apr, 2026 Reviewers agreed at journal 01 Apr, 2026 Reviewers agreed at journal 01 Apr, 2026 Reviewers agreed at journal 01 Apr, 2026 Reviewers agreed at journal 01 Apr, 2026 Reviewers invited by journal 01 Apr, 2026 Editor assigned by journal 01 Apr, 2026 Submission checks completed at journal 30 Mar, 2026 First submitted to journal 28 Mar, 2026 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-9252526","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":618439425,"identity":"932ac44b-3a35-4c17-b393-15d509008a99","order_by":0,"name":"S. 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