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      Crayfish optimization based pixel selection using block scrambling based encryption for secure cloud computing environment

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          Abstract

          Cloud Computing (CC) is a fast emerging field that enables consumers to access network resources on-demand. However, ensuring a high level of security in CC environments remains a significant challenge. Traditional encryption algorithms are often inadequate in protecting confidential data, especially digital images, from complex cyberattacks. The increasing reliance on cloud storage and transmission of digital images has made it essential to develop strong security measures to stop unauthorized access and guarantee the integrity of sensitive information. This paper presents a novel Crayfish Optimization based Pixel Selection using Block Scrambling Based Encryption Approach (CFOPS-BSBEA) technique that offers a unique solution to improve security in cloud environments. By integrating steganography and encryption, the CFOPS-BSBEA technique provides a robust approach to secure digital images. Our key contribution lies in the development of a three-stage process that optimally selects pixels for steganography, encodes secret images using Block Scrambling Based Encryption, and embeds them in cover images. The CFOPS-BSBEA technique leverages the strengths of both steganography and encryption to provide a secure and effective approach to digital image protection. The Crayfish Optimization algorithm is used to select the most suitable pixels for steganography, ensuring that the secret image is embedded in a way that minimizes detection. The Block Scrambling Based Encryption algorithm is then used to encode the secret image, providing an additional layer of security. Experimental results show that the CFOPS-BSBEA technique outperforms existing models in terms of security performance. The proposed approach has significant implications for the secure storage and transmission of digital images in cloud environments, and its originality and novelty make it an attractive contribution to the field. Furthermore, the CFOPS-BSBEA technique has the potential to inspire further research in secure cloud computing environments, making the way for the development of more robust and efficient security measures.

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          A novel triple-image encryption and hiding algorithm based on chaos, compressive sensing and 3D DCT

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            Robust medical image encryption based on DNA-chaos cryptosystem for secure telemedicine and healthcare applications

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              Improving data hiding within colour images using hue component of HSV colour space

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                Author and article information

                Contributors
                vikassoman@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                18 January 2025
                18 January 2025
                2025
                : 15
                : 2406
                Affiliations
                Department of Instrumentation Engineering, Madras Institute of Technology Campus, Anna University, ( https://ror.org/01qhf1r47) Chromepet, Chennai 44, India
                Article
                86956
                10.1038/s41598-025-86956-2
                11742954
                39827314
                62ddb943-817b-472e-be49-438f2b473cec
                © The Author(s) 2025

                Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

                History
                : 17 July 2024
                : 15 January 2025
                Categories
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                © Springer Nature Limited 2025

                Uncategorized
                pixel selection,cloud computing,crayfish optimization,steganography,image encryption,salp swarm algorithm,engineering,mathematics and computing

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