Fingerprint-based robust medical image watermarking in hybrid transform

Vaidya, S. Prasanth

doi:10.1007/s00371-022-02406-4

Cited by 48 publications

(13 citation statements)

References 45 publications

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“…Vaidya [25] presented a hybrid transform-based medical image watermarking which embeds the patient's fingerprint in the medical images using lifting wavelet transform (LWT) and DWT. The experimental results show the PSNR values in the range of 36 dB for watermarked medical images.…”

Section: Related Workmentioning

confidence: 99%

Secure Medical Image Communication Using Fragile Data Hiding Based on Discrete Wavelet Transform and A₅ Lattice Vector Quantization

2023

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Secure communication of medical images is essential to telemedicine. Message Authentication Codes (MAC) can be embedded inside medical images to protect their integrity. Fragile watermarking algorithms are suitable options since they can be used to detect any tampering attempt. In this paper, a novel fragile data-hiding algorithm based on Integer-to-Integer Discrete Wavelet Transforms (IIDWT) and A 5 Lattice Vector Quantization (LVQ) is proposed. In the proposed data-hiding algorithm, a combination of the medical image Metadata and a MAC is embedded into the medical image. The Metadata includes information about the patient such as name, family, birthday, the place where it is created such as the name of the hospital, and the physician's name. To preserve the privacy of the patients and the physician/hospital, the Metadata is then replaced with fake information. The receiver can extract the Metadata and the MAC. If the extracted MAC is the same as the expected MAC, the integrity of the medical image is guaranteed. Otherwise, a tampering attempt is detected. The proposed algorithm can embed 50% more data than similar algorithms in medical images while keeping the Peak Signal to Noise Ratio (PSNR) in acceptable ranges. Furthermore, the proposed algorithm is applied to a dataset of medical images and high PSNR values above 53.88 dB are experienced.INDEX TERMS Data hiding, privacy, medical image privacy, fragile data hiding, integer discrete wavelet transforms, lattice vector quantization.

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Section: Related Workmentioning

confidence: 99%

Secure Medical Image Communication Using Fragile Data Hiding Based on Discrete Wavelet Transform and A₅ Lattice Vector Quantization

2023

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“…Recently, in 2022, ref. [19] S. Prasanth Vaidya presented a novel adaptive watermarking system utilizing a hybrid transform and patient fingerprint as a watermark intended for electronic health care techniques. The proposed algorithm shows its robustness and authentication with numerous medical image assaults.…”

Section: Related Workmentioning

confidence: 99%

Signing and Verifying Encrypted Medical Images Using Double Random Phase Encryption

Abdallah

Elkamchouchi

2022

Entropy

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Digital Signature using Self-Image signing is introduced in this paper. This technique is used to verify the integrity and originality of images transmitted over insecure channels. In order to protect the user’s medical images from changing or modifying, the images must be signed. The proposed approach uses the Discrete Wavelet Transform to subdivide a picture into four bands and the Discrete Cosine Transform DCT is used to embed a mark from each sub-band to another sub-band of DWT according to a determined algorithm. To increase the security, the marked image is then encrypted using Double Random Phase Encryption before transmission over the communication channel. By verifying the presence of the mark, the authority of the sender is verified at the receiver. Authorized users’ scores should, in theory, always be higher than illegal users’ scores. If this is the case, a single threshold might be used to distinguish between authorized and unauthorized users by separating the two sets of scores. The results are compared to those obtained using an approach that does not employ DWT.

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“…The digital reform of hospitals has provided easy access to medical information, as well as improve the efficiency and accuracy of medical information expression. Medical images, one of the products of digital hospitals, store private information such as pathological characteristics of patients and are a vital basis for doctors to diagnose patients' conditions [3,4]. However, there is a risk of malicious tampering, illegal copying, and information leakage of medical images in network transmission.…”

Section: Introductionmentioning

confidence: 99%

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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Fingerprint-based robust medical image watermarking in hybrid transform

Cited by 48 publications

References 45 publications

Secure Medical Image Communication Using Fragile Data Hiding Based on Discrete Wavelet Transform and A₅ Lattice Vector Quantization

Secure Medical Image Communication Using Fragile Data Hiding Based on Discrete Wavelet Transform and A₅ Lattice Vector Quantization

Signing and Verifying Encrypted Medical Images Using Double Random Phase Encryption

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

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