2D-CTM and DNA-Based Computing for Medical Image Encryption

EasyChair Preprint 8539

Abstract

Medical imaging plays an important role in the proper treatment of a patient's disease. Nowadays, the virtual diagnosis of patients is becoming popular, so these images are sent from one place to another via the network for diagnosis purposes. So, the medical images need to be secured from any illegal access and modification. To handle this situation, a novel key generation with medical image encryption and decryption algorithms is proposed based on chaos, DNA computing, and Mersenne Twister (MT). The key is generated using a proposed new 2D-Chaotic Tan Map (2D-TCM). Then, the image is passed through two levels of confusion and diffusion based on DNA computing, chaos, and MT to get a final, highly secured encrypted image. Extensive comparative evaluation of the results is performed on X-ray images and MRI images using different security metrics, such as key space, key sensitivity, histogram analysis, entropy and correlation analysis. The results show that the proposed model achieved a better result in comparison to other related techniques.

Keyphrases: DNA, Encryption, Security, chaotic map, medical image

@booklet{EasyChair:8539,
  author    = {Mobashshirur Rahman and Piyush Kumar},
  title     = {2D-CTM and DNA-Based Computing for Medical Image Encryption},
  howpublished = {EasyChair Preprint 8539},
  year      = {EasyChair, 2022}}