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Medical Image Encryption using Chaotic Map Improved Advanced Encryption Standard.pdf (1.55 MB)

Medical image encryption using chaotic map improved advanced encryption standard

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journal contribution
posted on 2018-08-08, 10:34 authored by Ranvir S. Bhogal, Baihua LiBaihua Li, Alastair G. Gale, Yan Chen
Under the Digital Image and Communication in Medicine (DICOM) standard, the Advanced Encryption Standard (AES) is used to encrypt medical image pixel data. This highly sensitive data needs to be transmitted securely over networks to prevent data modification. Therefore, there is ongoing research into how well encryption algorithms perform on medical images and whether they can be improved. In this paper, we have developed an algorithm using a chaotic map combined with AES and tested it against AES in its standard form. This comparison allowed us to analyse how the chaotic map affected the encryption quality. The developed algorithm, CAT-AES, iterates through Arnold’s cat map before encryption a certain number of times whereas, the standard AES encryption does not. Both algorithms were tested on two sets of 16-bit DICOM images: 20 brain MRI and 26 breast cancer MRI scans, using correlation coefficient and histogram uniformity for evaluation. The results showed improvements in the encryption quality. When encrypting the images with CAT-AES, the histograms were more uniform, and the absolute correlation coefficient was closer to zero for the majority of images tested on.

History

School

  • Science

Department

  • Computer Science

Published in

international Journal of Information Technology and Computer Science(IJITCS)

Citation

BHOGAL, R.S. ... et al, 2018. Medical image encryption using chaotic map improved advanced encryption standard. International Journal of Information Technology and Computer Science (IJITCS), 10 (8), pp.1-10.

Publisher

© Modern Education and Computer Science (MECS) Press

Version

  • VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/

Publication date

2018

Notes

This is an Open Access Article. It is published by MECS Press under the Creative Commons Attribution 4.0 International Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/

ISSN

2074-9007

eISSN

2074-9015

Language

  • en