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Leveraging chaos for enhancing encryption and compression in large cloud data transfers

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Abstract

One of the routine exercises to manage and improve the performance and utility of the cloud is the migration or transfer of cloud data whether it is large or small. However, it is extremely challenging to protect both data privacy and integrity concurrently while moving cloud data, particularly when it is very vast. Collectively, prior works fail to offer a complete solution to these problem. Even though data encryption and steganography techniques are popular and efficient, they provide higher time and space complexities and introduce information loss. As a result, the goal of this research is to provide a chaos compression and encryption system based on chaos theory to guarantee both data privacy and integrity during the transit or migration of massive cloud data. During data transmission, the entire data are compressed using a chaotic substitution box followed by an adaptive Huffman encoding algorithms. Therefore, the input data are efficiently transformed into a non-readable form which replaces the original data, making it difficult for an unethical individual or group to determine its true sense. Our evaluation results show that the proposed chaotic technique has a maximum entropy value of 7.99, which supports its ability to provide more privacy when compared to previous techniques. It also delivers the best bits per code of 4.41, a throughput of 2.89 MB/s, and a minimal information loss percentage of 0.0011%, demonstrating its superior time, space efficiency, and ability to improve data integrity over existing methods.

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All of the data utilized in this study were collected from open sources. The relevant download URLs are shown in Table 5 of “Appendix”.

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Author notes

  1. Tanupriya Choudhury

    Present address: Professor (Research), CSE Dept., Graphic Era Deemed to be University, Dehradun, Uttarakhand, 248002, India

Authors and Affiliations

  1. School of Computer Science, University of Petroleum and Energy Studies (UPES), Dehradun, Uttarakhand, 248007, India

    Shiladitya Bhattacharjee

  2. CSE Department, IIT Jodhpur, Jodhpur, Rajasthan, India

    Himanshi Sharma

  3. CSE Dept., Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, Maharashtra, 412115, India

    Tanupriya Choudhury

  4. School of EECS, Queen Mary University of London, London, UK

    Ahmed M. Abdelmoniem

  5. Faculty of Computers and Information, Assiut University, Assiut, Egypt

    Ahmed M. Abdelmoniem

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  1. Shiladitya Bhattacharjee
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  2. Himanshi Sharma
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  4. Ahmed M. Abdelmoniem
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Contributions

This study was collaboratively developed, carried out, and presented by Shiladitya Bhattacharjee and Himanshi Sharma. Tanupriya Choudhury helped by providing insightful comments. Ahmed M. Abdelmoniem contributed extensively to the writing, organization, editing, review, and revisions of this manuscript.

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Correspondence to Shiladitya Bhattacharjee or Ahmed M. Abdelmoniem.

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Bhattacharjee, S., Sharma, H., Choudhury, T. et al. Leveraging chaos for enhancing encryption and compression in large cloud data transfers. J Supercomput (2024). https://doi.org/10.1007/s11227-024-05906-3

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