Optimized Hybrid Cryptography for Cloud Data Security: ECC-AES Integration with Performance Evaluation

Optimized Hybrid Cryptography for Cloud Data Security: ECC-AES Integration with Performance Evaluation | 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 Optimized Hybrid Cryptography for Cloud Data Security: ECC-AES Integration with Performance Evaluation Aysha Muryam, Kong Weiqiang, Rayan Rasheed This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9110341/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 Cloud computing enables convenient data storage but introduces security challenges. Some proposed security solutions for protecting cloud environ- ments are in the literature. However, these methods may not be suitable for a wide range of applications in a cloud environment due to their high computing and communication overheads, because if the security protocol is strengthened, it inversely impacts performance and vice versa. Further- more, these security frameworks are vulnerable to several attacks and also lack strong user anonymity and privacy protection for the end user. To ad- dress these issues, we proposed a novel hybrid approach combining Elliptic Curve Cryptography (ECC) and the Advanced Encryption Standard (AES), referred to as the ECC-AES approach. Our novel approach will overcome these issues without increasing computational power and cost. Experiments show that including Encryption Time, Decryption Time, and computational power demonstrate that ECC-AES not only shows high performance but also achieves high classification accuracy under various cryptographic attacks. Specifically, ECC-AES performs really well and achieves a 40% reduction in encryption time and 45% reduction in decryption time, and a maximum of 35–45% of energy consumption as compared to existing methods. Cloud Security Hybrid Cryptography Data Confidentiality Cloud Computing Elliptic Curve Cryptography Advanced Encryption Standard Energy Efficiency Full Text Additional Declarations No competing interests reported. Supplementary Files table1.jpg table2.jpg table3.jpg table4.jpg table1.jpg main.bib.bib 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-9110341","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":605423999,"identity":"b1fdbfa1-9581-4e1d-a21a-c6c5a75703f3","order_by":0,"name":"Aysha 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