A lightweight chaos-based medical image encryption scheme using random shuffling and XOR operations

Fawad Masood, Maha Driss, Wadii Boulila, Jawad Ahmad*, Sadaqat Ur Rehman, Sana Ullah Jan, Abdullah Qayyum, William J. Buchanan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Medical images possess significant importance in diagnostics when it comes to healthcare systems. These images contain confidential and sensitive information such as patients’ X-rays, ultrasounds, computed tomography scans, brain images, and magnetic resonance imaging. However, the low security of communication channels and the loopholes in storage systems of hospitals or medical centres put these images at risk of being accessed by unauthorized users who illegally exploit them for non-diagnostic purposes. In addition to improving the security of communication channels and storage systems, image encryption is a popular strategy adopted to ensure the safety of medical images against unauthorized access. In this work, we propose a lightweight cryptosystem based on Henon chaotic map, Brownian motion, and Chen’s chaotic system to encrypt medical images with elevated security. The efficiency of the proposed system is proved in terms of histogram analysis, adjacent pixels correlation analysis, contrast analysis, homogeneity analysis, energy analysis, NIST analysis, mean square error, information entropy, number of pixels changing rate, unified average changing intensity, peak to signal noise ratio and time complexity. The experimental results show that the proposed cryptosystem is a lightweight approach that can achieve the desired security level for encrypting confidential image-based patients’ information.
Original languageEnglish
Number of pages28
JournalWireless Personal Communications
Early online date19 May 2021
DOIs
Publication statusE-pub ahead of print - 19 May 2021

Keywords

  • lightweight cryptosystem
  • Henon chaotic map
  • Chen's chaotic system
  • Brownian motion
  • cryptographic technique
  • medical image

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