Table of Content

Open Access

ARTICLE

A Robust Zero-Watermarking Based on SIFT-DCT for Medical Images in the Encrypted Domain

Jialing Liu1, Jingbing Li1,2,*, Yenwei Chen3, Xiangxi Zou1, Jieren Cheng1,2, Yanlin Liu1, Uzair Aslam Bhatti1,2
College of Information Science and Technology, Hainan University, Haikou, 570228, China.
State key Laboratory of Marine Resource Utilization in the South China Sea, Hainan University, Haikou, 570228, China.
Graduate School of Information Science and Engineering, Ritsumeikan University, Shiga, Japan.
* Corresponding Author: Jingbing Li. Email: .

Computers, Materials & Continua 2019, 61(1), 363-378. https://doi.org/10.32604/cmc.2019.06037

Abstract

Remote medical diagnosis can be realized by using the Internet, but when transmitting medical images of patients through the Internet, personal information of patients may be leaked. Aim at the security of medical information system and the protection of medical images, a novel robust zero-watermarking based on SIFT-DCT (Scale Invariant Feature Transform-Discrete Cosine Transform) for medical images in the encrypted domain is proposed. Firstly, the original medical image is encrypted in transform domain based on Logistic chaotic sequence to enhance the concealment of original medical images. Then, the SIFT-DCT is used to extract the feature sequences of encrypted medical images. Next, zero-watermarking technology is used to ensure that the region of interest of medical images are not changed. Finally, the robust of the algorithm is evaluated by the correlation coefficient between the original watermark and the attacked watermark. A series of attack experiments are carried out on this method, and the results show that the algorithm is not only secure, but also robust to both traditional and geometric attacks, especially in clipping attacks.

Keywords

Robustness, CT Image, zero-watermarking, SIFT-DCT, encrypted domain

Cite This Article

J. Liu, J. Li, Y. Chen, X. Zou, J. Cheng et al., "A robust zero-watermarking based on sift-dct for medical images in the encrypted domain," Computers, Materials & Continua, vol. 61, no.1, pp. 363–378, 2019.

Citations




This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 2042

    View

  • 1265

    Download

  • 0

    Like

Share Link

WeChat scan