A Zero Watermarking Scheme for Encrypted Medical Images Based on Tetrolet-DCT

Cui, Wenfeng; Liu, Jing; Li, Jingbing; Fang, Yangxiu; Dan, Yi; Xiao, Xinping; Bhatti, Uzair Aslam; Han, Baoru

doi:10.1007/978-981-16-3013-2_8

Cited by 2 publications

(15 citation statements)

References 6 publications

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“…Our algorithm can still extract complete watermark information when the rotation angle reaches 70°, as shown in Table 4. As can be seen from Figure 16c, the algorithm proposed in this paper significantly outperforms algorithms [18][19][20] and DWT-DCT in resisting the rotation attack. For the scaling attack, as can be seen from Figure 16d, algorithms [18,19] and DWT-DCT slightly outperform our algorithm.…”

Section: Algorithm Comparisonmentioning

confidence: 84%

“…As can be seen from Figure 16c, the algorithm proposed in this paper significantly outperforms algorithms [18][19][20] and DWT-DCT in resisting the rotation attack. For the scaling attack, as can be seen from Figure 16d, algorithms [18,19] and DWT-DCT slightly outperform our algorithm. For Y-axis and Xaxis shear attacks, our algorithms show good performance.…”

Section: Algorithm Comparisonmentioning

confidence: 84%

“…For Y-axis shear attacks, our algorithm significantly outperforms algorithms [18,20] and DWT-DCT. For X-axis cropping, our algorithm outperforms both algorithms [18][19][20] and DWT-DCT, as shown in Figures 16e,f. The algorithm in Ref.…”

Section: Algorithm Comparisonmentioning

confidence: 98%

“…Poor performance of cropping attacks Tetrolet-DCT [18] 2021 Good invisibility and robustness Relatively poor performance of rotation attacks DWT-SVD [17] 2021 Good performance of conventional attacks Poor performance of translation attacks…”

Section: Spatial Domain Lsb-dwt [10] 2022 Good Robustness Of Gaussian...mentioning

confidence: 99%

“…Qin et al [19] performed DCT transform on the coarse layer of Curvelet transform to extract robust feature vectors with energy concentration in the low-frequency part, and the algorithm has good robustness against conventional and geometric attacks, where the performance of X-axis shear attack is poor. Cui et al [18] proposed an algorithm for encrypting medical image watermarking based on Tetrolet transform and DCT using DFT to encrypt the original image. Zermi et al [17] proposed a watermarking algorithm based on DWT-SVD that applies SVD to the low-frequency (LL) sub-band of the DWT transform and then integrates the watermark into the lowest significant bits of the S component obtained by combining the parity of consecutive coefficients, which is well resistant to rotation and pretzel noise attacks.…”

Section: Introductionmentioning

confidence: 99%

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Robust zero‐watermarking algorithm based on discrete wavelet transform and daisy descriptors for encrypted medical image

Yuan,

Li,

Liu

et al. 2024

CAAI Trans on Intel Tech

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In the intricate network environment, the secure transmission of medical images faces challenges such as information leakage and malicious tampering, significantly impacting the accuracy of disease diagnoses by medical professionals. To address this problem, the authors propose a robust feature watermarking algorithm for encrypted medical images based on multi‐stage discrete wavelet transform (DWT), Daisy descriptor, and discrete cosine transform (DCT). The algorithm initially encrypts the original medical image through DWT‐DCT and Logistic mapping. Subsequently, a 3‐stage DWT transformation is applied to the encrypted medical image, with the centre point of the LL3 sub‐band within its low‐frequency component serving as the sampling point. The Daisy descriptor matrix for this point is then computed. Finally, a DCT transformation is performed on the Daisy descriptor matrix, and the low‐frequency portion is processed using the perceptual hashing algorithm to generate a 32‐bit binary feature vector for the medical image. This scheme utilises cryptographic knowledge and zero‐watermarking technique to embed watermarks without modifying medical images and can extract the watermark from test images without the original image, which meets the basic requirements of medical image watermarking. The embedding and extraction of watermarks are accomplished in a mere 0.160 and 0.411s, respectively, with minimal computational overhead. Simulation results demonstrate the robustness of the algorithm against both conventional attacks and geometric attacks, with a notable performance in resisting rotation attacks.

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