Open Access

ARTICLE

Medical Image Transmission Using Novel Crypto-Compression Scheme

Arwa Mashat¹, Surbhi Bhatia^2,*, Ankit Kumar³, Pankaj Dadheech³, Aliaa Alabdali⁴

1 Department of Information Systems, College of Computing and Information Technology, King Abdulaziz University, Rabigh, Saudi Arabia
2 Department of Information Systems, College of Computer Sciences and Information Technology, King Faisal University, Saudi Arabia
3 Department of Computer Science & Engineering, Swami Keshvanand Institute of Technology, Management & Gramothan, Jaipur, Rajasthan, India
4 Department of Information Technology, College of Computing and Information Technology, King Abdulaziz University, P.O. Box 344, Rabigh 21911, Saudi Arabia

* Corresponding Author: Surbhi Bhatia. Email:

(This article belongs to the Special Issue: New Trends in Artificial Intelligence and Deep learning for Instrumentation, Sensors, and Robotics)

Intelligent Automation & Soft Computing 2022, 32(2), 841-857. https://doi.org/10.32604/iasc.2022.021636

Received 08 July 2021; Accepted 31 August 2021; Issue published 17 November 2021

Abstract

The transmission of medical records over indiscrete and open networks has caused an increase in fraud involving stealing patients’ information, owing to a lack of security over these links. An individual’s medical documents represent confidential information that demands strict protocols and security, chiefly to protect the individual’s identity. Medical image protection is a technology intended to transmit digital data and medical images securely over public networks. This paper presents some background on the different methods used to provide authentication and protection in medical information security. This work develops a secure cryptography-based medical image reclamation algorithm based on a combination of techniques: discrete cosine transform, steganography, and watermarking. The novel algorithm takes patients’ information in the form of images and uses a discrete cosine transform method with artificial intelligence and watermarking to calculate peak signal-to-noise ratio values for the images. The proposed framework uses the underlying algorithms to perform encryption and decryption of images while retaining a high peak signal-to-noise ratio value. This value is hidden using a scrambling algorithm; therefore, a unique patient password is required to access the real image. The proposed technique is demonstrated to be robust and thus able to prevent stealing of data. The results of simulation experiments are presented, and the accuracy of the new method is demonstrated by comparisons with various previously validated algorithms.

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Keywords

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