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Current Signal Transduction Therapy

Editor-in-Chief

ISSN (Print): 1574-3624
ISSN (Online): 2212-389X

Research Article

A Secure Reversible Data Hiding and Encryption System for Embedding EPR in Medical Images

Author(s): Sonal Ayyappan, C. Lakshmi and Varun Menon*

Volume 15, Issue 2, 2020

Page: [124 - 135] Pages: 12

DOI: 10.2174/1574362414666190304162411

Abstract

Background: Recent advances in medical associated technologies have drastically increased the amount of electronic medical records collected, stored and transferred through the network. Considering the significance and level of sensitivity of the collected medical data, the security of the transmitted data has become a very vital and challenging task for researchers. The protection of these medical images with embedded data is usually guaranteed using encryption or data hiding techniques. Conventional techniques that employ encryption or data hiding are often insecure and also time-consuming during transmission through the network.

Materials and Methods: A method combining encryption and data hiding together can result in compression of data that reduces the transmission time and increases the security level. Reversible data hiding in images can reestablish the cover image after extracting the hidden embedded data exclusive of alterations. Here a new reversible crypto-watermarking system is proposed using cryptographic algorithms that encrypts and hides an Electronic Patient Record (EPR) into an image corresponding to that patient using Rhombus Prediction Scheme. It embeds a big amount of encrypted data into an image with hardly noticeable modification using spatial pixel manipulations based on prediction errors. The marked image is hashed using SHA-256 algorithm.

Results and Conclusion: Hashing and cryptography increases the robustness and guarantees authenticity with integrity. The proposed method results in improved safety with a lower transmission time than the existing methods.

Keywords: Crypto-watermarking, Diffie-Hellman, image security, medical images, RC4 encryption, rhombus prediction scheme, SHA-256.

Graphical Abstract
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