A Privacy-Preserving and Secure Framework using Blockchain-based Quantum-inspired Complex Convolutional Neural Network for IoT-driven Smart Cities

A Privacy-Preserving and Secure Framework using Blockchain-based Quantum-inspired Complex Convolutional Neural Network for IoT-driven Smart Cities | 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 Privacy-Preserving and Secure Framework using Blockchain-based Quantum-inspired Complex Convolutional Neural Network for IoT-driven Smart Cities Chandra Prakash Singh, Rohita Yamaganti, Lokendra Singh Umrao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6332750/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Nov, 2025 Read the published version in Peer-to-Peer Networking and Applications → Version 1 posted 11 You are reading this latest preprint version Abstract The developments of IoT, smart cities have become majority of urbanization. IoT networks use the Internet as an open channel to enable distributed smart devices to collect, process data inside architecture of smart cities. In this manuscript, Privacy-Preserving and Secure Framework utilizing Blockchain-depend Quantum-inspired Complex Convolutional Neural Network for IoT-driven Smart Cities (PSF-BCH-QICCN-IoT) is proposed. Initially the dataset is gathering from BoT-IoT dataset. The gathered data is fed to block chain based Proof-of-Monitoring (PoM) for Privacy-Preserving and Secure Framework. Then feature mapping and feature selection is done by Hunger Game Search Optimization Algorithm (HGSOA). After that, QICCN is utilized for classifying anomaly likes Denial-of-Service, Distributed DoS, Normal, Reconnaissance and Theft. Generally, QICCN doesn’t show some optimization adaption techniques to determine optimum parameter to offer accurate detection. Firebug Swarm Optimization process (FSO) is proposed to enhance QICCN classifies the anomaly precisely. The performance of proposed technique is analyzed utilizing performance metrics likes accuracy, specificity, recall, precision, F1-score, false alarm rate. The proposed PSF-BCH-QICCN-IoT method attains 23.33%, 21.45% and 31.35% higher accuracy; 34.15%, 32.26% and 19.95% higher precision;25.55%, 27.35% and 22.15% higher recall analyzed to the existing methods, like developing effectual feature engineering along machine learning technique for identifying IoT-botnet cyber-attacks (DMLP -IoT-BAD), feature engineering depend performance analysis of ML-DL processes for Botnet attack identification in IoMT ( SVM– IoT-BAD) and intrusion identification scheme for IoT botnet attacks utilizing deep learning (DNN - IoT-BAD) respectively. Firebug Swarm Optimization Hunger Game Search Optimization Algorithm Quantum-inspired Complex Convolutional Neural Network Proof-of-Monitoring Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 11 Nov, 2025 Read the published version in Peer-to-Peer Networking and Applications → Version 1 posted Editorial decision: Revision requested 08 Jul, 2025 Reviews received at journal 07 Jul, 2025 Reviews received at journal 02 Jul, 2025 Reviewers agreed at journal 12 Jun, 2025 Reviews received at journal 12 Jun, 2025 Reviewers agreed at journal 12 Jun, 2025 Reviewers agreed at journal 07 Jun, 2025 Reviewers invited by journal 06 Jun, 2025 Editor assigned by journal 10 Apr, 2025 Submission checks completed at journal 09 Apr, 2025 First submitted to journal 29 Mar, 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-6332750","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":467833403,"identity":"eb210f47-0675-4270-be62-993ef748877e","order_by":0,"name":"Chandra Prakash Singh","email":"","orcid":"","institution":"P.K. 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