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Soft Computing

16-05-2023 | Focus

Cloud data transmission based on security and improved routing through hybrid machine learning techniques

Authors: Shamimul Qamar, Mohd Amaan, Mohammed Inamur Rahman, Ibrahim Aqeel, Mohammed Shuaib, Ibrahim Mohsen Khormi, Shadab Alam

Published in: Soft Computing

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Abstract

A shared environment and the computer paradigm are combined in cloud computing (CC), enabling multiple users to access services and resources. This ecosystem is not only globally accessible via the Internet, but it can also be shared at all levels. All levels of resources, platforms, and infrastructure can be traded with a variety of clients. This research propose novel method in cloud data transmission with security and enhance routing by hybrid machine learning techniques. Here, the cryptographic-based cloud architecture and routing for data analysis is carried out using hybrid of support auto-encoder gradient neural networks. The experimental analysis in terms of data transmission ratio, specificity, training accuracy, validation accuracy, security analysis. Proposed technique attained data transmission ratio of 65%, specificity of 78%, training accuracy of 93%, validation accuracy of 83%, and security analysis of 65%.

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Metadata
Title
Cloud data transmission based on security and improved routing through hybrid machine learning techniques
Authors
Shamimul Qamar
Mohd Amaan
Mohammed Inamur Rahman
Ibrahim Aqeel
Mohammed Shuaib
Ibrahim Mohsen Khormi
Shadab Alam
Publication date
16-05-2023
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-023-08417-0

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