Proposed Watermarking Method Research Articles

Robust image tamper detection and recovery with self-embedding watermarking using SPIHT and LDPC

In today’s digital landscape, the pervasive use of digital images across diverse domains has led to growing concerns regarding their authenticity and reliability. The potential for malicious manipulation of these images underscores the critical need to develop robust methods for detecting tampering and ensuring their integrity. Fragile watermarking has been found to have extensive applications for tamper detection and recovery. An image watermarking technique for tamper detection, correction, and recovery is presented in this study. The proposed method employs a self-embedding method to generate the reference watermark from the original image, which has the advantage of superior tamper detection, localization, recovery capabilities, and robustness against attacks. Set Partitioning in the Hierarchical Tree (SPIHT) algorithm is applied to generate a reference watermark of the original image. Low-Density Parity Check (LDPC) is employed for error correction, providing higher-quality reconstruction to recover the original image. Schur decomposition processed the watermarked image blocks to generate authentication bits for each block to enhance tampering detection. The proposed watermarking method was evaluated using PSNR, SSIM, BER, and NC metrics for grayscale and colored images. The technique demonstrated high robustness in tamper detection and recovery against various malicious attacks. Comparative analysis with existing methods shows the efficacy of the proposed method.

A statistical characteristics preserving watermarking scheme for time series databases

Database watermarking is one of the most effective methods to protect the copyright of databases. However, traditional database watermarking has a potential drawback: watermark embedding will change the distribution of data, which may affect the use and analysis of databases. Considering that most analyses are based on the statistical characteristics of the target database, keeping the consistency of the statistical characteristics is the key to ensuring analyzability. Since statistical characteristics analysis is performed in groups, compared with traditional relational databases, time series databases (TSDBs) have obvious time-grouping characteristics and are more valuable for analysis. Therefore, this paper proposes a robust watermarking algorithm for time series databases, effectively ensuring the consistency of statistical characteristics. Based on the time-group characteristics of TSDBs, we propose a three-step watermarking method, which is based on linear regression, error compensation, and watermark verification, named RCV. According to the properties of the linear regression model and error compensation, the proposed watermark method generates a series of data that have the same statistical characteristics. Then, the verification mechanism is performed to validate the generated data until it conveys the target watermark message. Compared with the existing methods, our method achieves superior robustness and preserves constant statistical properties better.r.

A novel watermarking framework for intellectual property protection of NLG APIs

Natural language generation (NLG) models have attracted extensive attention and applications due to their combination with powerful deep learning techniques. Many NLG models are encapsulated in cloud APIs serving commercial organizations, which have become very important profitable services for these institutions. However, cloud platforms may suffer from model extraction attacks that aim to imitate the functionality of these NLG models in practical applications, thus infringing the intellectual property (IP) of the NLG APIs. Unfortunately, most current watermarking methods for protecting deep model IP are not directly applicable to IP protection of NLG APIs. In addition, the semantic similarity between the watermarked texts generated by the baseline method and the original texts is not high enough, which can be easily detected by attackers. To make up these gaps, we propose a novel watermarking framework which embeds watermarks by conducting lexical modification to the outputs of the NLG models, and uses the corresponding watermark identification method can identify the attackers and protect the IP of NLG APIs. Experiment result shows that our proposed watermarking method not only generates watermarked texts with higher semantically similar to the original texts but also achieves better identifiable performance compared with the baseline method. In addition, our watermarking method also exhibits outstanding performance in other aspects such as transferability, watermark undetectability and robustness.

Detection-Performance Tradeoff for Watermarking in Industrial Control Systems

The watermarking method, which adds unique watermarks to data, has been widely used for integrity attack detection in industrial control systems (ICSs). Existing literature generally designs watermarking mechanisms without considering the existence of noises, which cannot be trivially applied to realistic ICS scenarios in the presence of strong noise interference. On one hand, the low-intensity watermarking will be ineffective under the strong noise environment; while on the other hand, the oversized watermarking can possibly degrade the control performance or even destabilize the system. Therefore, the intensity of watermarks plays a fundamental role in balancing the tradeoff between detection effectiveness and control performance, which, to the best of our knowledge, has never been thoroughly analyzed yet. To this end, in this paper, we for the first time propose an optimal watermarking design method for ICSs considering the detection-performance tradeoff. To begin with, we shift the watermark container from data points to segments and update the detection metrics to reduce the noise impact. Then, we formulate an optimization problem to determine the strength of watermarks to balance the detection-performance tradeoff. Meanwhile, the detection effectiveness and control performance metrics are analytically modeled and theoretically analyzed considering the discrepancy between added watermarks and noises, signal quality, detection latency, as well as estimation of detection metrics. Finally, extensive numerical simulations and systematical experiments based on a practical Ethanol Distillation ICS are conducted to validate the theoretical analysis and demonstrate the outperformance of our proposed watermarking method in comparison with related works.

Robust Watermarking Method for Secure Transmission of Medical Images in EHR Systems

Confidentiality of Electronic Health Record (EHR) and privacy are two important security requirements for healthcare systems. Many devices on the EHR network utilize little or no encryption, which makes data in transit vulnerable to exploitative attacks, such as Man-in-the-Middle and other filtration methods. Recently, watermarking algorithms as an efficient response to these requirements is in the underline. In this paper, we present a robust watermarking method conceived as part of an Electronic Health Record platform. In this method a chaotic encryption and blind medical image watermarking technique was incorporated into the system as an authorization mechanism to ensure confidentiality and integrity of electronic health information. We present a hybrid watermarking method based on a combination of discrete wavelet transform (DWT), hessenberg Decomposition (HD), Singular value decomposition (SVD) and an original chaos crypto system based on the Arnold Transform (AT) of Singular Value Decomposition. In order to spread the robustness of our algorithm and provide additional security, an improved SVD-AT embedding and extraction procedure has been used to scramble the EHR data in the preprocessing step of the proposed method. In the process of watermark embedding, an R-level discrete wavelet transform was applied to the host image. The low frequency wavelet coefficients are selected to carry this scrambled-watermark. In extraction process, the stored used plain image is obtained from the trusted authority server to complete the verification process. The receiver should compare the unsigned watermark with the extracted watermark again. The verification can be done before clinical procedures and diagnosis. The proposed watermarking method endures entirety attacks and rightly extracts the hidden watermark without significant degradation in the image quality, thus, when the Peak Signal to Noise Ratio (PSNR) and Normalized Correlation (NC) performance of the proposed algorithm is performed.

A New Method for Image Protection Using Periodic Haar Piecewise-Linear Transform and Watermarking Technique.

The paper presents a novel data-embedding method based on the Periodic Haar Piecewise-Linear (PHL) transform. The theoretical background behind the PHL transform concept is introduced. The proposed watermarking method assumes embedding hidden information in the PHL transform domain using the luminance channel of the original image. The watermark is embedded by modifying the coefficients with relatively low values. The proposed method was verified based on the measurement of the visual quality of an image with a watermark with respect to the length of the embedded information. In addition, the bit error rate (BER) is also considered for different sizes of a watermark. Furthermore, a method for the detection of image manipulation is presented. The elaborated technique seems to be suitable for applications in digital signal and image processing where high imperceptibility and low BER are required, and information security is of high importance. In particular, this method can be applied in systems where the sensitive data is transmitted or stored and needs to be protected appropriately (e.g., in medical image processing).

Robust audio watermarking scheme based on fractional Charlier moment transform and dual tree complex wavelet transform

The popular embedded watermarking method in transform domains such as DWT, LWT, DCT, and SVD achieves copyright protection of audio signals by embedding watermarks into the original audio signals. The main weaknesses of the existing methods include low payload and low robustness against common audio processing operations and attacks, especially, vulnerability to shifting attack. This paper proposes a new robust, secure, and blind audio watermarking scheme based on a novel hybrid transform which is a combination of the dual tree complex wavelet transform (DTCWT) and the fractional Charlier moment transform (FrCMT). After segmenting the original audio signal into several segments of the same length, the 3-level DTCWT is applied on each segment using filters designed specifically to have shift invariance, then FrCMT is applied on the approximation coefficients of DTCWT. Finally, a sequence of watermark bits is embedded in FrCMT coefficients by quantizing their relative energy. The fractional order in FrCMT is chosen in our scheme in a way to obtain high imperceptibility and robustness against most common audio processing operations and attacks. Moreover, it is used as a security key to ensure a high security level of the proposed scheme. The comparative analysis confirms the high robustness, security, and efficiency of the proposed watermarking method.

Multiple Zero-Watermarking of Medical Images for Internet of Medical Things

The Internet of Medical Things (IoMT) plays a vital role in healthcare systems to increase electronic devices’ accuracy, reliability, and productivity. This paper presents fast multiple zero-watermarking methods based on Multi-channel Fractional Legendre Fourier moments (MFrLFMs) for medical image security and copyright protection in IoMT applications without deforming the original medical images. The MFrLFMs are utilized due to their high accuracy, numerical stability, geometric invariances, and high resistance to various attacks. Based on the most significant features generated from MFrLFMs, after scrambling using a two-dimensional Discrete Henon Map, then XORed with binary scrambled watermark to construct owner share. The proposed watermarking method is implemented using a low-cost Raspberry Pi Linux microprocessor, which ensures the suitability of medical devices in the IoMT environment. We evaluated the robustness of the proposed algorithm against different geometric and common signal processing attacks using various medical images. The proposed method gives better BER, NC, and SSIM values than existing methods.

An Improved Medical Image Watermarking Technique Based on Weber’s Law Descriptors

In distributed m-health communication, it is a major challenge to develop an efficient blind watermarking method to protect the confidential medical data of patients. This paper proposes an efficient blind watermarking for medical images, which boasts a very high embedding capacity, a good robustness, and a strong imperceptibility. Three techniques, namely, discrete cosine transform (DCT), Weber’s descriptors (WDs), and Arnold chaotic map, were integrated to our method. Specifically, the Arnold chaotic map was used to scramble the watermark image. Then, the medical image was partitioned into non-over lapping blocks, and each block was subjected to DCT. After that, the scrambled watermark image data were embedded in the middle-band DCT coefficients of each block, such that two bits were embedded in each block. Simulation results show that the proposed watermarking method provides better imperceptibility, robustness, and computational complexity results with higher embedding capacity than the contrastive method.

Enhanced Dct Image Watermarking Scheme Based on Zonal Sampling Algorithm Applied With Sspce Contour Extraction, Ramer and Adaptive Triangle Contour Compression Methods

This paper proposes an image watermarking scheme based on DCT transform and selected zonal sampling algorithms. The scheme used LPF and HPF transform coefficients in a certain geometric zone of the original image are retained. All the rest of the parameter is set to zero (0), quantized and transmitted where the watermark will be embedded. In order to test robustness, some attacks are performed. However, prior to the watermark extraction process, the attacked watermarked image will be subdued into contour processing methods using Single Step Parallel Contour Extraction, Ramer and Adaptive Triangle algorithms. The proposed method for contour compression will help enhance image recognition, security and especially where time (speed) is an essential factor. The results show that the proposed watermarking method is robust and secure against various signal/image processing attacks with PSNR values of approximately 35 dB with NCC values of 0.60 and above. In addition, experimental results from contour compression indicate that the proposed Adaptive Triangle method has a high compression ratio without significant visible distortion

A Voxel-Based Watermarking Scheme for Additive Manufacturing

Digital and analog contents, generated in additive manufacturing (AM) processes, may be illegally modified, distributed, and reproduced. In this article, we propose a watermarking scheme to enhance the security of AM. Compared with conventional watermarking methods, our algorithm possesses the following advantages. First, it protects geometric models and printed parts as well as G-code programs. Secondly, it embeds watermarks into both polygonal and volumetric models. Thirdly, our method is capable of creating watermarks inside the interiors and on the surfaces of complex models. Fourth, the watermarks may appear in various forms, including character strings, cavities, embossed bumps, and engraved textures. The proposed watermarking method is composed of the following steps. At first, the input geometric model is converted into a distance field. Then, the watermark is inserted into a region of interest by using self-organizing mapping. Finally, the watermarked model is converted into a G-code program by using a specialized slicer. Several robust methods are also developed to authenticate digital models, G-code programs, and physical parts. These methods perform virtual manufacturing, volume rendering, and image processing to extract watermarks from these contents at first. Then, they employ similarity evaluation and visual comparison to verify the extracted signatures. Some experiments had been conducted to validify the proposed watermarking method. The test results, analysis, discussion, and comparisons are also presented in this article.

Rapid and Blind Watermarking Approach of the 3D Objects Using QR Code Images for Securing Copyright.

Watermarking techniques in a wide range of digital media was utilized as a host cover to hide or embed a piece of information message in such a way that it is invisible to a human observer. This study aims to develop an enhanced rapid and blind method for producing a watermarked 3D object using QR code images with high imperceptibility and transparency. The proposed method is based on the spatial domain, and it starts with converting the 3D object triangles from the three-dimensional Cartesian coordinate system to the two-dimensional coordinates domain using the corresponding transformation matrix. Then, it applies a direct modification on the third vertex point of each triangle. Each triangle's coordinates in the 3D object can be used to embed one pixel from the QR code image. In the extraction process, the QR code pixels can be successfully extracted without the need for the original image. The imperceptibly and the transparency performances of the proposed watermarking algorithm were evaluated using Euclidean distance, Manhattan distance, cosine distance, and the correlation distance values. The proposed method was tested under various filtering attacks, such as rotation, scaling, and translation. The proposed watermarking method improved the robustness and visibility of extracting the QR code image. The results reveal that the proposed watermarking method yields watermarked 3D objects with excellent execution time, imperceptibility, and robustness to common filtering attacks.

Desynchronization Attacks Resilient Watermarking Method Based on Frequency Singular Value Coefficient Modification

Desynchronization is a very challenging type of attack in audio watermarking. The traditional singular value decomposition (SVD) based audio watermarking methods embed the watermark information by modifying the singular value of individual segment, which have little resistance against desynchronization attacks. In this paper, we propose a novel frequency singular value coefficient (FSVC) feature, which reflects the ratio between the singular values of two consecutive segments and is insensitive to desynchronization attacks, to carry the watermark bits. To our best knowledge, it is the first time that the ratio between singular values is employed for audio watermarking. In the proposed method, the discrete cosine transform (DCT) is performed on two consecutive segments of the host audio signal and SVD is applied to the DCT coefficients of the mid frequency band of each segment to extract the FSVC. Then the watermark bits are embedded by adjusting the values of the FSVC. The watermark embedding procedure is optimized to minimize the perceptual quality degradation and an error buffer is created to enhance the robustness. As a result, the proposed method can achieve a much higher embedding capacity than the existing methods tackling desynchronization attacks. The impact of desynchronization and common signal processing attacks on the proposed watermarking method is mathematically modeled, and the effectiveness of the proposed method against these attacks is theoretically and experimentally validated.

Robust Blind Speech Watermarking via FFT-Based Perceptual Vector Norm Modulation With Frame Self-Synchronization

Watermarking is an important measure for protecting proprietary digital multimedia data. This paper presents a novel approach to achieving robust and imperceptible blind speech watermarking on a frame-by-frame basis. The proposed method employs two modules operating in the fast Fourier transform (FFT) domain. The first module is referred to as downward progressive quantization index modulation. It modulates the vector norms drawn from FFT coefficients according to a guideline deduced from human auditory masking properties. The second module is referred to as boundary-constrained iterative adjustment. It provides a smooth transition across frames in the resulting speech waveform. Experiment results confirm the imperceptibility of the proposed modulation scheme in terms of the mean opinion score - listening quality objective (MOS-LQO) based on the perceptual evaluation of speech quality (PESQ) metric. The proposed watermarking method matched and exceeded the performance of five state-of-the-art methods in terms of robustness against common speech processing attacks.

New Color Image Zero-Watermarking Using Orthogonal Multi-Channel Fractional-Order Legendre-Fourier Moments

Zero-watermarking methods provide promising solutions and impressive performance for copyright protection of images without changing the original images. In this paper, a novel zero-watermarking method for color images is envisioned. Our envisioned approach is based on multi-channel orthogonal Legendre Fourier moments of fractional orders, referred to as MFrLFMs. In this method, a highly precise Gaussian integration method is utilized to calculate MFrLFMs. Then, based on the selected accurate MFrLFMs moments, a zero-watermark is constructed. Due to their accuracy, geometric invariances, and numerical stability, the proposed MFrLFMs-based zero-watermarking method shows excellent resistance against various attacks. Performed experiments using the proposed watermarking method show the outperformance over existing watermarking algorithms.

Significant difference-based watermarking in multitoned images

Digital multitoning is an advanced form of halftoning-based printing technique which renders multiple tones at each pixel of an image. This superior scheme delivers an improved print quality in terms of smooth texture, homogeneity and the suppression of artefacts. This Letter examines the potential scope of multitoning as an effective strategy to embed a binary watermark within a multitoned image. The proposed method uses the significant difference among the highpass wavelet coefficients achieved by discrete wavelet transform for watermark embedding. Furthermore, an improvised ordered dithering technique using adaptive threshold quantisation is also incorporated, which not only makes the proposed method time-efficient but also offers uniformity to the final image. The proposed watermarking technique is imperceptible and yields watermarked images with high peak signal-to-noise ratio value. Experimental simulations demonstrate that the proposed watermarking method is superior to the state-of-the-art methods in the context of both objective and subjective assessments.

A novel blind color image watermarking based on Walsh Hadamard Transform

A new blind color image watermarking based on Walsh Hadamard Transform (WHT) is proposed in this paper which uses Triangular Vertex Transform (TVT) along with WHT. This method introduces a Triangular Vertex Transform (TVT) and Inverse Triangular Vertex Transform (ITVT) as well as applies this transform for image watermarking. Initially, convert the R, G, B color image to TVT coefficients U, V and W using the proposed TVT transform. Then the W coefficient is subdivided into 4 × 4 non-overlapping blocks, which are then transformed using WHT. The watermark is encrypted with the key K using the 2D-Logistic Sine Coupling Map encryption to obtain the encrypted watermarked image. The bits of the encrypted image is embedded in the first row WHT coefficients since the embedding of watermark bit on the first row provides high robustness to attacks. After embedding the data, the inverse WHT and inverse TVT are applied to obtain the watermarked image. The extraction process is similar to that of the embedding process where TVT is applied on the Watermarked image to construct W′ coefficient. Subdivide the attained W′ coefficient into 4 × 4 sub-block and then the WHT is applied to the 4 × 4 sub-block for extracting the data from the first row of WHT coefficients. The performance of the proposed watermarking algorithm outperforms in terms of Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM) and Normalized cross-correlation (NC). Experimental results reveal that the proposed watermarking method is highly resistant to different types of attacks.

Invisible Medical Image Watermarking using Edge Detection And Discrete Wavelet Transform Coefficients

Protection and authentication of medical images is essential for the patient’s disease identification and diagnosis. The watermark in medical imaging application needs to be invisible and it is also required to preserve the low and high frequency features of image data which makes watermarking a difficult assignment. Within this manuscript an unseen medical image watermarking approach is projected apply edge detection in the discrete wavelet transform domain. The wavelet transform is brought into play to decay the medical picture interested in multi-frequency secondary band coefficients. The edge detection applies to high frequency wavelet group in the direction of generating the boundary coefficients used as a key. The Gaussian noise pattern is utilized as watermark as well as embedded within the edge coefficients around the edges. To add the robustness scaled dilated edge coefficient is added with the edge coefficients to generate the watermarked image. Preserving the small frequency secondary band fulfills the information requirement of the medical imaging application. At the same time as adding together the watermark during high frequency sub-bands improve the watermark invisibility. To add additional robustness the dilation is applied on the edged coefficient before being embedded with sub band coefficients. presentation of the technique is experienced on the dissimilar set of medical imagery as well as evaluation of the proposed watermarking method founds it robust not in favor of the different attacks such at the same time as filtering, turning round plus resizing. Parametric study foundation going on Mean Square Error along with Signal to Noise Ratio shows that how good method performs for invisibility.

Resilient Color Image Watermarking Using Accurate Quaternion Radial Substituted Chebyshev Moments

In this work, a new quaternion-based method for color image watermarking is proposed. In this method, a novel set of quaternion radial substituted Chebyshev moments (QRSCMs) is presented for robust geometrically invariant image watermarking. An efficient computational method is proposed for highly accurate, fast, and numerically stable QRSCMs in polar coordinates. The proposed watermarking method consists of three stages. In the first stage, the Arnold transform is used to improve the security of the watermarking scheme by scrambling the binary watermark. In the second stage, the proposed accurate and stable QRSCMs of the host color image are computed. In the third stage, the encrypted binary watermark is embedded into the host image by employing the quantization technique on selected-magnitude QRSCMs where the watermarked color image is obtained by adding the original host color image to the compensation image. Then, the binary watermark can be extracted directly without using the original image from the magnitudes of QRSCMs. Numerical experiments are performed where the performance of proposed method is compared with the existing quaternion moment-based watermarking methods. The comparison clearly shows that the proposed method is very efficient in terms of the visual imperceptibility capability and the robustness under different attacks compared to the existing quaternion moment-based watermarking algorithms.

An optimized hierarchical encryption technique for tamper recognition

Digital images contain sensitive information that needs to be watermarked for ownership authentication and copyright verification. It is crucial to have a method to detect and recognize tampering when images are sent over insecure channels. The watermarking scenario becomes more complicated when an intruder is precluded from obtaining a watermark signal from a watermarked image since it can expose future point-to-point correspondences. The proposed scheme utilizes a hierarchical strategy for improving the security of the semi-fragile watermarking scheme that requires fewer data to be exchanged before each transaction. Consequently, the proposed watermarking method obtains a trade-off between robustness and imperceptibility by using a meta-heuristic approach, namely, the Sine Cosine Algorithm (SCA). Furthermore, an Artificial Neural Network (ANN) is built using the Softmax classifier to recognize possible attacks that might be performed by an intruder. The whole scheme is presented in the form of a GUI with the attack recognition triggered from the receiver’s side. Experimental results show improved image quality metrics like PSNR, correlation coefficient, and structural similarity when the scaling factor used in the watermarking algorithm is optimized using SCA.