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Ben Said, Lamjed
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Electrical & Electronics Engineering

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Journal : Bulletin of Electrical Engineering and Informatics

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Secure Euclidean random distribution for patients’ magnetic resonance imaging privacy protection Tayh Albderi, Ali Jaber; Ben Said, Lamjed
Bulletin of Electrical Engineering and Informatics Vol 13, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i2.5989

Abstract

Patients’ information and images transfer among medical institutes represent a major tool for delivering better healthcare services. However, privacy and security for healthcare information are big challenges in telemedicine. Evidently, even a small change in patients’ information might lead to wrong diagnosis. This paper suggests a new model for hiding patient information inside magnetic resonance imaging (MRI) cover image based on Euclidean distribution. Both least signification bit (LSB) and most signification bit (MSB) techniques are implemented for the physical hiding. A new method is proposed with a very high level of security information based on distributing the secret text in a random way on the cover image. Experimentally, the proposed method has high peak signal to noise ratio (PSNR), structural similarity index metric (SSIM) and reduced mean square error (MSE). Finally, the obtained results are compared with approaches in the last five years and found to be better by increasing the security for patient information for telemedicine.
Co-Authors Tayh Albderi, Ali Jaber