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An efficient and secure compression technique for data protection using burrows-wheeler transform algorithm

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submitted on 2023-12-11, 06:25 and posted on 2023-12-13, 08:24 authored by M Baritha Begum, N. Deepa, Mueen Uddin, Rajesh Kaluri, Maha Abdelhaq, Raed Alsaqour

Data stored on physical storage devices and transmitted over communication channels often have a lot of redundant information, which can be reduced through compression techniques to conserve space and reduce the time it takes to transmit the data. The need for adequate security measures, such as secret key control in specific techniques, raises concerns about data exposure to potential attacks. Encryption plays a vital role in safeguarding information and maintaining its confidentiality by utilizing a secret key to make the data unreadable and unalterable. The focus of this paper is to tackle the challenge of simultaneously compressing and encrypting data without affecting the efficacy of either process. The authors propose an efficient and secure compression method incorporating a secret key to accomplish this goal. Encoding input data involves scrambling it with a generated key and then transforming it through the Burrows-Wheeler Transform (BWT). Subsequently, the output from the BWT is compressed through both Move-To-Front Transform and Run-Length Encoding. This method blends the cryptographic principles of confusion and diffusion into the compression process, enhancing its performance. The proposed technique is geared towards providing robust encryption and sufficient compression. Experimentation results show that it outperforms other techniques in terms of compression ratio. A security analysis of the technique has determined that it is susceptible to the secret key and plaintext, as measured by the unicity distance. Additionally, the results of the proposed technique showed a significant improvement with a compression ratio close to 90% after passing all the test text files.

Other Information

Published in: Heliyon
License: http://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1016/j.heliyon.2023.e17602

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Language

  • English

Publisher

Cell Press

Publication Year

  • 2023

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • University of Doha for Science and Technology
  • College of Computing and Information Technology - UDST

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