Geometric Attacks Research Articles

Attack-Defending Contrastive Learning for Volumetric Medical Image Zero-Watermarking

Zero-watermarking is an emerging distortion-free copyright protection method for volumetric medical images. However, achieving both robustness against various malicious attacks and distinguishability between individual images remains challenging. In this paper, we propose a novel attack-defending contrastive learning zero-watermarking scheme (ADCL-ZW) to tackle the above challenge using deep learning-based representations. In our approach, we design an attack-defending data enrichment mechanism to enhance the watermarking robustness by generating a large number of image samples under various watermarking attacks. Subsequently, features for both watermarking distinguishability and robustness are enhanced through application of a contrastive loss. In particular, we implement a dual-stream Siamese network architecture to effectively handle both signal attacks and geometric attacks in order to enhance the wartermarking performance. Experimental results demonstrate that ADCL-ZW achieves stronger watermarking robustness and a better tradeoff between watermarking robustness and distinguishability compared with state-of-the art zero-watermarking methods. One of the highlighted metrics the false negative rate of ADCL-ZW achieves 0.01 when a fixed false positive rate is set to 1%, which is more than 13.3 times better than the benchmark methods.

Redistributed invariant redundant fractional wavelet transform and its application in watermarking algorithm

In this paper, we introduce an invariant wavelet transform with multiple parameters in fractional domain and apply it to watermarking algorithm. First, we propose a new transform called redistributed invariant redundant fractional wavelet transform (RI-RFrWT) based on redistributed invariant integer wavelet transform (RI-IWT) and redundant fractional wavelet transform (RFrWT) which implements the extension of RI-IWT in the fractional domain. When the transform order of RI-RFrWT is 0, it degenerates to RI-IWT and has invariance. Second, RI-RFrWT is applied to the proposed optimized watermarking algorithm. This algorithm solves the problem that it is difficult for existing algorithms to show high robustness under both geometric and noise attacks. Third, a secure encryption algorithm based on Logisitic-adjusted-Sine map (LASM) and generalized Arnold transform (GAT) is designed to encrypt the information of watermark. Highly sensitive LASM and multi-parameter GAT improve the security of the watermarking algorithm. To improve the invisibility and robustness of the algorithm, particle swarm optimization (PSO) is also used to simultaneously improve the order of RI-RFrWT and embedding strength. Last, the simulation results demonstrate that the proposed watermarking method outperforms high invisibility, robustness and security. Compared with the relevant literature, it has obvious advantages in invisibility and resistance to geometric attacks and noise attacks.

A Compressed Domain Robust Video Watermarking Resists Geometric Attack

The widespread utilization of mobile devices and the proliferation of video content, facilitated by communication networks, has unfortunately led to issues such as data piracy, illegal usage, and unauthorized sharing. To address these challenges, digital watermarking emerges as a crucial tool, serving purposes such as authentication, maintaining integrity, and identifying rightful owners. In the realm of video watermarking, two primary categories exist: watermarking in the compressed domain and watermarking in the uncompressed domain. Compressed domain watermarking involves expedited data processing through partial video decoding, whereas uncompressed domain watermarking requires more time. This article proposes a novel video watermarking methodology designed specifically to withstand geometric attacks. The proposed method aims to dynamically embed watermarks within video content, thereby enhancing resilience against various geometric distortions. Geometric attacks, including scaling, rotation, cropping, and translation, pose significant challenges in digital watermarking and are thus a focal point of this research. The objective is to integrate this approach with complex video coding standards, leveraging compression domain techniques to fortify resistance against geometric attacks. Tests show that the suggested video watermarking system works well. Not only does it excel in safeguarding against geometric attacks, but it also mitigates perceptual quality degradation, thus ensuring a balance between robustness and visual fidelity. As the prevalence of video content continues to grow, robust watermarking techniques like the one presented here play a vital role in preserving intellectual property rights and ensuring the integrity of multimedia content in the digital age.

Resnet50 and logistic Gaussian map-based zero-watermarking algorithm for medical color images

Medical image copyright protection is becoming increasingly relevant as medical images are used more frequently in medical networks and institutions. The traditional embedded watermarking system is inappropriate for medical images since it degrades the original images’ quality. Furthermore, medical-colored image watermarking options are constrained since most medical watermarking systems are built for gray-scale images. This paper proposes a zero-watermarking scheme for medical color image copyright protection based on a chaotic system and Resnet50, which is a convolutional neural network method. The network Resnet50 is used to extract features from the color medical image, and then a logistic Gaussian map is used to scramble these features and scramble the binary image. Finally, an exclusive OR operation is performed (scrambled binary image, scrambled features for the medical color image) to form a zero watermarking. The experimental result proves that our scheme is effective and robust to geometric and common image processing attacks. The BER values of the extracted watermarks are below 0.0039, and the NCC values are above 0.9942, while the average PSNR values of the attacked images are 29.0056 dB. Also, it is superior to other zero-watermark schemes for medical images in terms of robustness to conventional image processing and geometric attacks. Furthermore, the experimental results show that the Resnet50 model outperforms other models in terms of reducing the mean squared errors of the features between the attacked and original image.

Watermarking Algorithm for Remote Sensing Images based on Ring-Shaped Template Watermark and Multiscale LCM

Identifying template watermarks under severe geometric distortions is a significant scientific problem in the current watermarking research for remote sensing images. We propose a novel watermarking algorithm that integrates the ring-shaped template watermark with the multiscale local contrast measure (LCM) method. In the embedding stage, the ring-shaped template watermark is embedded into the discrete Fourier transform (DFT) magnitude coefficients, converting the watermark into small targets in the DFT domain. During the detection stage, the multiscale LCM, a classic infrared small target detection method, enhances these small targets and generates a contrast map. Peak detection is then performed on the contrast map to determine the radius of the template watermark. Finally, circular edge local binarization is applied to extract the watermark information. The proposed method enables synchronization recovery of watermarks under blind conditions. The experimental results demonstrate that the method possesses strong robustness against various geometric attacks such as rotation, scaling, translation, and cropping. It outperforms comparative algorithms in terms of robustness and also exhibits good imperceptibility.

INVARIANT ZERO-WATERMARKING ALGORITHM IN DWT-DCT DOMAIN USING ROBUST FEATURES MATCHING

In order to protect the copyright of the digital contents, the robust watermarking techniques are employed based on frequency domains or combined frequency domains. Another techniques, called zero-watermarking which does not modify the original image to embed the watermark but create a watermark from its robust features, is a useful technique for resolving the tension between robustness and invisibility. In this paper, we propose a new zero-watermarking algorithm based on discrete wavelet transform and discrete cosine transform domain with significant feature points matching for improving the robustness. In our proposed method, the original image is firstly separated into three components (Y, Cr, Cb), then its Y-component is performed with discrete wavelet transform, afterwards its LL3 is transformed with discrete cosine transform. To generate the master share of the original image, the DCT-based image is binarized. After performing the Arnold transformation on the watermark, the owner share is generated by taking the XOR operation on the scrambled watermark and master share. The robustness of the our proposed algorithm for imaging processes is analyzed, and the results show that the proposed algorithm is robust to common signal processing such as noise, filtering, JPEG compression, geometric attacks such as rotation, scaling, translation and so on.

Research on Variable Parameter Color Image Encryption Based on Five-Dimensional Tri-Valued Memristor Chaotic System.

To construct a chaotic system with complex characteristics and to improve the security of image data, a five-dimensional tri-valued memristor chaotic system with high complexity is innovatively constructed. Firstly, a pressure-controlled tri-valued memristor on Liu's pseudo-four-wing chaotic system is introduced. Through analytical methods, such as Lyapunov exponential map, bifurcation map and attractor phase diagram, it is demonstrated that the new system has rich dynamical behaviors with periodic limit rings varying with the coupling parameter of the system, variable airfoil phenomenon as well as transient chaotic phenomenon of chaos-periodic depending on the system parameter and chaos-quasi-periodic depending on the memristor parameter. The system is simulated with dynamic circuits based on Simulink. Secondly, the differently structured synchronous controls of chaotic systems are realized using a nonlinear feedback control method. Finally, based on the newly constructed five-dimensional chaotic system, a variable parameter color image encryption scheme is proposed to iteratively generate varying chaotic pseudo-random sequences by varying the system parameters, which will be used for repetition-free disambiguation, additive modulo left-shift diffusion and DNA encryption for the three components of RGB of the color image after chunking. The simulation results are analyzed by histogram, information entropy, adjacent pixel correlation, etc., and the images are tested using differential attack, noise attack and geometric attack, as well as analyzing the PSNR and SSIM of the decrypted image quality. The results show that the encryption method has a certain degree of security and can be applied to medical, military and financial fields with more complex environmental requirements.

A strategy for quantum watermarking against geometric attacks

The development of new quantum watermarking is in full swing, and it is crucial to test the robustness of these proposed watermarking schemes. In this paper, different quantum circuits are introduced to realize geometric transformations on quantum images, which serve as a means of simulating geometric attacks on quantum watermark images. Receivers may get distorted images, and the extracted watermark images may also be disrupted. To recover the geometric order of the quantum watermark images, a strategy is proposed to identify the trajectory of qubit alterations. Quantum circuits can be designed accordingly to restore the original order of the watermark images, which receivers could use before the extraction process to mitigate the impact of geometric attacks. Experimental simulations demonstrate how attacks affect the quantum watermark images and the extracted watermark images. Additionally, it illustrates how quantum recovery circuits step by step act on images that have been geometrically attacked. An analysis of the complexity of geometric restoration circuits reveals that quantum circuits exhibit better performance compared to classical circuits.

Hybrid watermarking and encryption techniques for securing three-dimensional information

A hybrid digital watermarking and encryption technique based on the Computer Generated Holography (CGH) and fractional Fourier transform (FRFT) combined with singular value decomposition (SVD) algorithm is proposed for securing three-dimensional (3D) information. Initially, hierarchical 3D information is encrypted using the angular spectrum diffraction method and a random phase key. This process yields a binary real valued CGH, where incorporating a random phase key broadens the key space and adds complexity, effectively scrambling and concealing the 3D information. Subsequently, the encrypted binary real valued CGH is embedded into the host image as a watermark using the FRFT-SVD algorithm. This hybrid approach enhances the security of the watermarking process. In the final step, the CGH watermark is extracted using the inverse operation of the embedding algorithm. Applying the correct optical key and angular spectrum inverse algorithm successfully reconstructs the 3D information. The watermark algorithm’s efficiency significantly improves by leveraging the rapid computational speed and high focusing capabilities of the FRFT. Additionally, integrating SVD enhances the image’s resistance to geometric attacks, thereby improving the algorithm’s invisibility and robustness. The proposed scheme effectively achieves the encryption and digital watermarking of 3D information. Simulation results substantiate the presented watermarking scheme’s efficacy and robustness.

Homomorphic encryption domain asymmetric fingerprinting scheme for 3D models of oblique photography

AbstractExisting copyright protection schemes for 3D models of oblique photography predominantly utilize digital watermarking technology, most of which suffer from shortcomings such as the potential false accusation of legitimate users and the inability to effectively trace unauthorized distributors. In response to these challenges, this article proposes a homomorphic encryption domain asymmetric fingerprinting scheme for 3D models of oblique photography. Initially, the fingerprints to be embedded are collaboratively generated by the transacting parties, with the publisher remaining unaware of the user's actual fingerprint. This approach ensures the effective implementation of the asymmetric nature of the fingerprinting scheme. Subsequently, potential geometric and non‐geometric attacks are considered prior to fingerprint embedding. Robustness is enhanced for the proposed solution through relative coordinate transformations and normalization procedures. Ultimately, the embedding and extraction of fingerprints are achieved through the application of an effective bit parity check method, in conjunction with the vertex‐paradigm projection length mapping mechanism and the Paillier homomorphic encryption system, minimizing embedding distortion while ensuring data security. Experimental results demonstrate that the proposed solution exhibits satisfying robustness against common manipulations, such as cropping, simplification, and geometric attacks. Additionally, the scheme effectively safeguards legitimate users from false accusations and accurately traces maliciously authorized users.

Bio-Inspired Watermarking Method for Authentication of Fundus Images in Computer-Aided Diagnosis of Retinopathy

Nowadays, medical imaging has become an indispensable tool for the diagnosis of some pathologies and as a health prevention instrument. In addition, medical images are transmitted over all types of computer networks, many of them insecure or susceptible to intervention, making sensitive patient information vulnerable. Thus, image watermarking is a popular approach to embed copyright protection, Electronic Patient Information (EPR), institution information, or other digital image into medical images. However, in the medical field, the watermark must preserve the quality of the image for diagnosis purposes. In addition, the inserted watermark must be robust both to intentional and unintentional attacks, which try to delete or weaken it. This work presents a bio-inspired watermarking algorithm applied to retinal fundus images used in computer-aided retinopathy diagnosis. The proposed system uses the Steered Hermite Transform (SHT), an image model inspired by the Human Vision System (HVS), as a spread spectrum watermarking technique, by leveraging its bio-inspired nature to give imperceptibility to the watermark. In addition, the Singular Value Decomposition (SVD) is used to incorporate the robustness of the watermark against attacks. Moreover, the watermark is embedded into the RGB fundus images through the blood vessel patterns extracted by the SHT and using the luma band of Y’CbCr color model. Also, the watermark was encrypted using the Jigsaw Transform (JST) to incorporate an extra level of security. The proposed approach was tested using the image public dataset MESSIDOR-2, which contains 1748 8-bit color images of different sizes and presenting different Diabetic Retinopathy (DR). Thus, on the one hand, in the experiments we evaluate the proposed bio-inspired watermarking method over the entire MESSIDOR-2 dataset, showing that the embedding process does not affect the quality of the fundus images and the extracted watermark, by obtaining average Peak Signal-to-Noise Ratio (PSNR) values higher to 53 dB for the watermarked images and average PSNR values higher to 32 dB to the extracted watermark for the entire dataset. Also, we tested the method against image processing and geometric attacks successfully extracting the watermarking. A comparison of the proposed method against state-of-the-art was performed, obtaining competitive results. On the other hand, we classified the DR grade of the fundus image dataset using four trained deep learning models (VGG16, ResNet50, InceptionV3, and YOLOv8) to evaluate the inference results using the originals and marked images. Thus, the results show that DR grading remains both in the non-marked and marked images.

Blind watermarking algorithm with 2D-SCCM chaotic system encryption based on SURF and RHFMs

In this paper, a digital watermarking algorithm was proposed based on local feature regions and radial harmonic Fourier moments. It used a quantized modulation algorithm to embed the watermark information into the frequency domain information of the image. Compared with traditional watermarks directly embedded into the pixel values, the algorithm enhanced the invisibility of the watermark. Many existing digital watermarking algorithms neglected the security of the embedding process, because of more attention on the effect of post-embedding and extraction. To overcome this problem, we proposed a two-dimensional hyperchaotic system named 2D-SCCM chaotic system, which used classical sine mapping and cubic mapping for coupling. Before embedding, the correlation among the pixels of the watermarked image was disrupted, resulting in a full process security enhancement. Combining the clustering algorithm with feature point extraction, the obtained local feature region was more stable and suitable for watermark embedding. Results showed that the improved watermark embedding algorithm was more effective for resisting geometric attacks such as cropping attacks. Moreover, the PSNR values of the final watermark-embedded images were all greater than 50 dB, indicating a good balance between imperceptibility and robustness.

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

AbstractIn 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.

Application of Zero-Watermarking Scheme Based on Swin Transformer for Securing the Metaverse Healthcare Data.

The existing medical image privacy solutions cannot completely solve the security problems created by applying the metaverse healthcare system. A robust zero-watermarking scheme based on the Swin Transformer is proposed in this paper to improve the security of medical images in the metaverse healthcare system. This scheme uses a pretrained Swin Transformer to extract deep features from the original medical images with a good generalization performance and multiscale, and binary feature vectors are generated by using the mean hashing algorithm. Then, the logistic chaotic encryption algorithm boosts the security of the watermarking image by encrypting it. Finally, an encrypted watermarking image is XORed with the binary feature vector to create a zero-watermarking, and the validity of the proposed scheme is verified through experimentation. According to the results of the experiments, the proposed scheme has excellent robustness to common attacks and geometric attacks, and implements privacy protections for medical image security transmissions in the metaverse. The research results provide a reference for the data security and privacy protection of the metaverse healthcare system.

A hybrid domain-based watermarking for vector maps utilizing a complementary advantage of discrete fourier transform and singular value decomposition

Digital watermarking plays a crucial role in the copyright protecting of vector maps. Due to its solid theoretical foundation, Discrete Fourier transform (DFT) is frequently used in the construction of watermarking scheme for diverse electronic data. However, when applied to vector maps, DFT is particularly vulnerable to local changes in coordinate points, posing challenges in surviving coordinate point attacks and limiting its practicality. Furthermore, its resistance against geometric attacks is quite weak. To address these issues, we propose an algorithmic complementary strategy that enhances the performance of DFT-based vector map watermarking scheme. The proposed scheme is founded upon a hybrid transform domain consisting of DFT and singular value decomposition (SVD). The first step is to extract feature points using the Douglas Peucker algorithm, with the distance threshold set to a relative value to ensure synchronization of feature points throughout scaling. The feature points are then subjected to DFT to obtain magnitude coefficients, which are then further transformed using SVD. By combining the geometric invariance of magnitude coefficients with the singular vectors of SVD, an invariant with rotation, scaling, and translation invariance can be generated. For watermark embedding, the invariant serves as an embedding domain and are multiplied to minimize the impact on the host vector maps. The experimental results reveal that the proposed vector map watermarking has very low disturbance, substantially lower than the comparing algorithms, deriving in excellent invisibility. The scheme can extract watermark images with a normalized correlation value of 1 under a variety of attacks, including rotation, scaling, translation, vertex addition, simplification, and map cropping, and it can even extract identifiable copyright information under a 10% vertex deletion, demonstrating very comprehensive robustness.

Robust multifunctional watermarking system based zero-watermarking and polar harmonic Fourier moments

The pseudo-randomness exhibited by chaotic systems has proven valuable not only in plaintext information encryption of images with varying dimensions but also as a key signal for protecting image copyright information. Image copyright protection is a crucial part of image information protection. Currently, digital watermarking technology is predominantly employed for copyright protection of digital images. However, most of the existing watermarking technologies primarily focus on the improvement of watermarking performance, neglecting the security of the watermarking system itself. Drawing inspiration from the Latin square rule, this paper proposes a novel hyperchaotic mapping modulation framework, which is employed to construct a new 3D hyperchaotic mapping and enhance the security of the fragile watermark and the zero-watermark generation process. Additionally, it is integrated into the classical image encryption framework of scrambling-diffusion to safeguard meaningful copyright information. Moreover, a functional watermarking system is designed based on the RSA asymmetric encryption algorithm, least significant bit (LSB), and polar harmonic Fourier moments (PHFMs). The proposed system enables identity verification, tampering location, and copyright authentication simultaneously. During the generation of zero watermarks, the binarization threshold of the PHFMs information matrix is determined by the method of maximum variance. The experimental results demonstrate that this scheme achieves a high level of security, better robustness to both conventional and geometric attacks, and precise localization for different types of tampering attacks.

Robust Reversible Watermarking by Fractional Order Zernike Moments and Pseudo-Zernike Moments

Robust reversible watermarking (RRW) is one of the most popular areas in information hiding. Existing schemes have two drawbacks: 1) schemes that can resist conventional attacks often fail to resist geometric attacks, and 2) schemes that can resist geometric attacks often are not robust against conventional attacks and have poor stability. Inspired by the high robustness of fractional-order orthogonal moments (FoOM) and the good feature of resistance to geometric attacks of Zernike moments and pseudo-Zernike moments (ZM/PZM), in this research, FoOM is used to optimize ZM/PZM to obtain FoZM/FoPZM (namely, fractional-order Zernike moments and fractional-order pseudo-Zernike moments). Furthermore, a denoiser is proposed to preprocess the watermarks to improve the robustness against geometric and conventional attacks, the amount of extracted auxiliary information is decreases and the extraction process of auxiliary information is designed to be more stable. Specifically, first, the source of the difference between the watermarked image and the carrier image is identified, that difference is represented with less information, and then that information is embedded into the cover image as auxiliary information. Second, the watermark is embedded in the low-order FoZM/FoPZM component. Finally, the watermarked image is denoised using a denoiser before extracting the watermark. The experimental results show that the scheme has good stability and strong robustness. Compared with existing methods, the proposed scheme has a small and stable auxiliary information size, strong robustness to noise attacks such as Gaussian noise and salt-and-pepper noise attacks, and better resistance to geometric attacks such as rotation and scaling attacks.

A novel geometrically invariant quantum watermarking scheme utilizing Quantum Error Correction

This paper proposes a novel geometrically invariant quantum watermarking scheme using Quantum Error Correction (QEC) and Novel Enhanced Quantum Image Representation (NEQR). The Geometric Transformation-based Image Assembling (GTA) mechanism is proposed to reconstruct the quantum watermark image utilizing QEC principle. The proposed GTA mechanism involves Quantum Image Rotation (QIR) and Quantum Block Rotation (QBR), thus two corresponding quantum watermarking methods, GTA_QIR and GTA_QBR, are proposed and detailed quantum circuits with complexity O(n) are designed. Then the Quantum Majority Finder (QMF) is proposed for embedding the watermark uniformly. In the experiments, we employ dataset USC-SIPI to evaluate the visual quality and robustness of the proposed scheme. Comparisons with the recent quantum watermarking methods is conducted and the results show that our methods have a superior performance. When under attack of ’Salt and Pepper’ noise addition, the proposed GTA_QIR and GTA_QBR improve the average Peak Signal-to-Noise Ratio (PSNR) by 22.57% and 23.49% at a density of 0.05, while at a density of 0.1, the average improvement is 11.13% and 12.05% respectively. Moreover, to the best of our knowledge, this is one of the first quantum watermarking scheme which demonstrates resistance to geometric attacks.

Hybrid watermarking algorithm for medical images based on digital transformation and MobileNetV2

The current study presents a new methodology for zero watermarking that relies on the discrete wavelet transform (DWT) and an improved MobileNetV2 convolutional neural network, along with the discrete cosine transform (DCT). This model is intended to overcome the issue of algorithm robustness in encrypted medical image watermarking. The proposed technique targets medical images inside the area of encryption and offers a unique watermarking approach to overcome the issues above. The coefficients acquired from the fully linked network layer are converted using DWT and DCT to create the medical image's feature vector. Second, MobileNetV2 is initially fed the medical image; this network has been prepared by adjusting parameters such as the convolution kernels' size and the convolution modules' typical architecture. Finally, the encryption of watermarks is achieved through the utilization of the logistic map system and hash function, whereby an independent party securely stores the requisite keys. The integration of a zero-watermark involves the execution of logical operations on both the encrypted watermarks and the attributes of the source image. The results of the experiment indicate that the algorithm can effectively differentiate encrypted medical images and recover the initial data from encrypted watermarked material despite conventional and geometric attacks. Compared to alternative algorithms, their superior resilience and invisibility are noteworthy.

Hybrid medical image zero watermarking via discrete wavelet transform-ResNet101 and discrete cosine transform

This paper suggests a way to move forward with medical images based on the discrete wavelet transform (DWT), ResNet101-DCT (discrete cosine transform), and zero watermarking. In addition, we extract deep medical image attributes using ResNet101, a pre-training network. Furthermore, deep features undergo a transformation via DWT and DCT, then a perceptual hash function is employed to generate the feature vector. The watermark is encrypted by chaotic scrambling the original watermark, an exclusive-OR (XOR) gate into the medical image, and generating and storing the logical key vector. Overall, the feature extraction technique is employed to extract the significant characteristics of the medical image under testing and develop the feature vector. Finally, the feature vector is subjected to an XOR maneuver with the logical key vector, deriving the encrypted watermark. Once the encrypted watermark has been obtained and decrypted, the restored watermark can be used to determine the medical image's ownership and watermark information by calculating the normalized correlation (NC) coefficient. Most NC values are greater than 0.50. The algorithm also shows good robustness against conventional and geometric attacks.