Analysis of Image Steganography Techniques for Different Image Format

Gupta, Lalit Kumar; Singh, Aniket; Kushwaha, Abhishek; Vishwakarma, Ashish

doi:10.1109/icaect49130.2021.9392492

Cited by 3 publications

(1 citation statement)

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“…The fast expansion of technology over the internet has resulted in a high difficulty for managing image data by researchers, especially in text transfer in telemedicine [1]. The hiding information techniques have significant achieving security especially that are send through internet to save from hackers [2]- [4]. A dedicated and novel algorithm is required to satisfy the new equipment.…”

Section: Introductionmentioning

confidence: 99%

Secure Euclidean random distribution for patients’ magnetic resonance imaging privacy protection

Tayh Albderi,

Ben Said

2024

Bulletin EEI

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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.

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Section: Introductionmentioning

confidence: 99%