Abstract
In order to solve the problem of patient information security protection in medical images, whilst also taking into consideration the unchangeable particularity of medical images to the lesion area and the need for medical images themselves to be protected, a novel robust watermarking algorithm for encrypted medical images based on dual-tree complex wavelet transform and discrete cosine transform (DTCWT-DCT) and chaotic map is proposed in this paper. First, DTCWT-DCT transformation was performed on medical images, and dot product was per-formed in relation to the transformation matrix and logistic map. Inverse transformation was undertaken to obtain encrypted medical images. Then, in the low-frequency part of the DTCWT-DCT transformation coefficient of the encrypted medical image, a set of 32 bits visual feature vectors that can effectively resist geometric attacks are found to be the feature vector of the encrypted medical image by using perceptual hashing. After that, different logistic initial values and growth parameters were set to encrypt the watermark, and zero-watermark technology was used to embed and extract the encrypted medical images by combining cryptography and third-party concepts. The proposed watermarking algorithm does not change the region of interest of medical images thus it does not affect the judgment of doctors. Additionally, the security of the algorithm is enhanced by using chaotic mapping, which is sensitive to the initial value in order to encrypt the medical image and the watermark. The simulation results show that the pro-posed algorithm has good homomorphism, which can not only protect the original medical image and the watermark information, but can also embed and extract the watermark directly in the encrypted image, eliminating the potential risk of decrypting the embedded watermark and extracting watermark. Compared with the recent related research, the proposed algorithm solves the contradiction between robustness and invisibility of the watermarking algorithm for encrypted medical images, and it has good results against both conventional attacks and geometric attacks. Under geometric attacks in particular, the proposed algorithm performs much better than existing algorithms.
Highlights
Nowdays, with the promotion of big data and cloud platforms, the use of modern diagnostic tools such as medical images to diagnose and predict diseases is more and more widely in the medical industry
Unlike the digital watermarking scheme in the plaintext domain which embedding and extraction of the watermark needs to be done by the owner of the watermark [Chen, Yin, He et al (2018)], with the homomorphism of encryption algorithm, watermark and carrier image in ciphertext state can be delivered to a trusted third party [Dai, Wang, Zhou et al (2016)]
By observing the low frequency coefficients of the encrypted images after transformation, we found that the values of the low frequency coefficients of encrypted brain images after Dual-tree complex wavelet transform (DTCWT)-DCT transformation varies greatly under various attacks, their symbols remain basically unchanged
Summary
With the promotion of big data and cloud platforms, the use of modern diagnostic tools such as medical images to diagnose and predict diseases is more and more widely in the medical industry. The robust digital watermarking technology of the plaintext medical image can only guarantee the security of the watermark information, ignoring the consideration of the carrier medical images. Unlike the digital watermarking scheme in the plaintext domain which embedding and extraction of the watermark needs to be done by the owner of the watermark [Chen, Yin, He et al (2018)], with the homomorphism of encryption algorithm, watermark and carrier image in ciphertext state can be delivered to a trusted third party [Dai, Wang, Zhou et al (2016)]. Based on the above reasons, we proposed a robust digital watermarking algorithm for encrypted medical images It adopts zero-watermark technology, and uses the dual-tree complex wavelet transform and Logistic chaotic map in the encryption domain. It has become the preferred transformation for the extraction of medical image features in this paper
Sign-in/Register to view highlights & summary 
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
