Advancing Robotic Swarms with Blockchain Technology: A Dynamic Two-Factor Authentication Consensus Framework

Advancing Robotic Swarms with Blockchain Technology: A Dynamic Two-Factor Authentication Consensus Framework | 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 Article Advancing Robotic Swarms with Blockchain Technology: A Dynamic Two-Factor Authentication Consensus Framework Marck Herzon Barrion, Argel Bandala, Jose Martin Maningo, Elmer Dadios, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5301694/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 Swarm robotics offers significant advantages by enhancing adaptability, scalability, and reliability. These systems excel in disaster response, environmental monitoring, and search and rescue operations, ensuring functionality despite the failure of individual robots. However, real-world deployment of swarm robotics is hindered by major communication security risks and concerns, making rigorous measures vital to prevent malicious attacks from compromising system integrity and effectiveness. Blockchain technology enhances data integrity and trust. This study introduces a robust Two-Factor Blockchain Consensus (2-FBC) framework, combining off-chain peer verification with an on-chain consensus mechanism. The framework dynamically adjusts peer similarity and trust scores, enabling reliable, decentralized consensus amidst the presence of Byzantine faults. With swarm robotic security research still in its infancy, this work aims to fill a fundamental gap, providing a solution to swarm vulnerabilities. Experimental evaluations using E-puck robots in the ARGoS simulator demonstrate the framework's effectiveness. The 2-FBC approach achieved a mean absolute error of 2.52% in scalability tests, improved accuracy by 19.62% in diverse and challenging environments, and maintained a low error rate of 2.32% against Byzantine attacks. Resource efficiency was confirmed through practical CPU and RAM usage metrics, with the blockchain ledger scaling predictably based on swarm size, ensuring compatibility with the storage capacities of the robots. The results validate the framework’s efficiency, establishing a solid foundation for new deployment opportunities in potentially adversarial environments. Physical sciences/Engineering/Electrical and electronic engineering Physical sciences/Mathematics and computing/Computer science swarm robotics blockchain technology Two-factor blockchain consensus communications security environmental surveillance Full Text Additional Declarations No competing interests reported. Supplementary Files SR2FBCSupplementaryBarrion.docx 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. 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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-5301694","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":378161850,"identity":"83aa2001-f754-4422-9698-43af0d1e19c8","order_by":0,"name":"Marck Herzon 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