Traditional Watermarking Algorithms Research Articles

VSTNet: Robust watermarking scheme based on voxel space transformation for diffusion tensor imaging images

Deep watermarking has been successfully applied to real-value domain (e.g., CT, MRI, DWI) medical images for copyright protection; however, manifold-value domain images, such as diffusion tensor imaging (DTI), have received less academic attention. The non-Euclidean nature of DTI images hinders deep models from generating plausible DTI images because it is difficult to guarantee that each generated DTI image voxel lies on a 3 × 3 symmetric positive definite manifold. In this paper, we propose a robust watermarking scheme based on voxel space transformation for DTI images. First, a voxel space transformation is proposed, which effectively solves the problem of fiber orientation estimation in Riemann networks for DTI images and obtains the eigenvalues and eigenvectors of each voxel using singular value decomposition (SVD) to transform the DTI voxels from the 3 × 3 symmetric positive definite manifold space to Euclidean space. Second, SVD is combined with a deep neural network to extract the high-level features of each voxel eigenvalue in the DTI images and embedding watermarking messages, avoiding the false positive errors problem in traditional watermarking algorithms based on an SVD transform. Finally, using a deep neural network combining multiscale dilated convolution, dense residual connection and channel attention, the algorithm demonstrates high robustness against various intentional or unintentional attacks on DTI images while ensuring the good visual quality and diffusion characteristics of the DTI images embedded with watermarking messages. Experiments show that the watermarking message extraction accuracy reaches 97.8% for Crop (p = 0.7) attacks and 95.4% for Gaussian Blur (k = 7) attacks.

Consistency preserving database watermarking algorithm for decision trees

Database watermarking technologies provide an effective solution to data security problems by embedding the watermark in the database to prove copyright or trace the source of data leakage. However, when the watermarked database is used for data mining model building, such as decision trees, it may cause a different mining result in comparison with the result from the original database caused by the distortion of watermark embedding. Traditional watermarking algorithms mainly consider the statistical distortion of data, such as the mean square error, but very few consider the effect of the watermark on database mining. Therefore, in this paper, a consistency preserving database watermarking algorithm is proposed for decision trees. First, label classification statistics and label state transfer methods are proposed to adjust the watermarked data so that the model structure of the watermarked decision tree is the same as that of the original decision tree. Then, the splitting values of the decision tree are adjusted according to the defined constraint equations. Finally, the adjusted database can obtain a decision tree consistent with the original decision tree. The experimental results demonstrated that the proposed algorithm does not corrupt the watermarks, and makes the watermarked decision tree consistent with the original decision tree with a small distortion.

Database Watermarking Algorithm Based on Decision Tree Shift Correction

With the transmission and sharing of data in the Internet of Things (IoT), while bringing development to life and the economy, it also inevitably threatens the data copyright protection and authentication. Digital watermarking technology can provide an effective solution for copyright protection by embedding the watermark in the data to prove the copyright attribution. The existing methods of digital watermarking in IoT mainly target multimedia, without considering the copyright authentication in database data. Unlike multimedia information, the database does not focus on the subjective visual perception when using the data, but rather on the potential values unlocked from the data through algorithms such as data mining. Therefore, we propose a new database watermarking algorithm based on decision tree shift correction (DTSC), considering the data copyright authentication and usability when applying for data mining algorithm. The algorithm adjusts the watermarked data by the DTSC method and makes the watermarked decision tree identical to the original in the iteration process. It solves the problem of database data copyright authentication in IoT and ensures the usability of the data when used for decision tree model construction. From the simulation results, it can be seen that the proposed method ensures the usability of the data for the classification and regression tree decision tree algorithm while embedding the watermark in the database data, and the data distortion of the proposed method does not differ from that of the traditional watermarking algorithm.

Mapping based Residual Convolution Neural Network for Non-embedding and Blind Image Watermarking

Traditional image watermarking algorithms directly modify the host image by watermark embedding, which is hard to balance the contradiction between the robustness and imperceptibility. Inspired by the human brain’s associative memory, this paper proposes a non-embedding and blind image watermarking algorithm via mapping based Residual Convolution Neural Network (Mapping-based RCNN). For preprocessing, median filter is applied on the host image to enhance the robustness of the algorithm to against various attacks. After that, Discrete Cosine Transform and Singular Value Decomposition are adopted to extract the corresponding image information matrix. To obtain the mapping relationship between host image and watermark image, the information matrix is input into the designed Mapping-based RCNN structure for network training. The Mapping-based RCNN is a non-embedding watermarking algorithm, which not only overcomes the imperceptibility shortcoming but also wins good robustness compared with traditional watermarking algorithms. Experimental results show that the proposed algorithm can successfully extract the watermark images under various attacks, and is more robust than existing watermarking algorithms.

Non-Linear-Echo Based Anti-Collusion Mechanism for Audio Signals

Collusion attacks are considered to be challenging attacks in audio copyright protection. The traditional watermarking algorithms cannot identify the traitors when other attacks, such as desynchronization attacks, are applied with a collusion attack. Instead of tracing the traitors, in this paper we aim to tackle collusion attacks by removing the commercial value from the colluded copy, which will demotivate the attackers from launching collusion attacks. Since the commercial value of an audio signal is directly reflected by its perceptual quality, we propose a novel non-linear-echo generation (NLEG) based algorithm to significantly degrade the perceptual quality of the colluded copy by embedding a time delay sequence into the host signal. The proposed NLEG is also designed to be resilient to common signal processing attacks and desynchronization attacks. Furthermore, the proposed NLEG can be combined with other digital watermarking techniques to enhance its performance on protecting the copyright information. Experimental results show the validity of the proposed NLEG.

Deep Template-Based Watermarking

Traditional watermarking algorithms have been extensively studied. As an important type of watermarking schemes, template-based approaches maintain a very high embedding rate. In such scheme, the message is often represented by some dedicatedly designed templates, and then the message embedding process is carried out by additive operation with the templates and the host image. To resist potential distortions, these templates often need to contain some special statistical features so that they can be successfully recovered at the extracting side. But in existing methods, most of these features are handcrafted and too simple, thus making them not robust enough to resist serious distortions unless very strong and obvious templates are used. Inspired by the powerful feature learning capacity of deep neural network, we propose the first deep template-based watermarking algorithm in this paper. Specifically, at the embedding side, we first design two new templates for message embedding and locating, which is achieved by leveraging the special properties of human visual system, i.e., insensitivity to specific chrominance components, the proximity principle and the oblique effect. At the extracting side, we propose a novel two-stage deep neural network, which consists of an auxiliary enhancing sub-network and a classification sub-network. Thanks to the power of deep neural networks, our method achieves both digital editing resilience and camera shooting resilience based on typical application scenarios. Through extensive experiments, we demonstrate that the proposed method can achieve much better robustness than existing methods while guaranteeing the original visual quality.

A novel watermarking algorithm based on characteristics model of local fragmentary images

Watermarking is a popular technology to protect the copyright of digital image from illegal infringement. Traditional watermarking algorithms cannot better resist the illegal tampering attacks, causing serious security issues. This paper aims to propose an image watermarking algorithm with ability against illegal tampering attacks. The original image should be firstly pre-processed, and its fragmentary characteristic function of local image block is used to generate watermark locations randomly. When the watermark is illegally tampered and damaged, the generated fragmentary characteristic factor can be used to re-construct the original image. Finally, the forensics of original image is realised. The experimental results show that the proposed algorithm can effectively embed a watermark into image. Besides, the original image can be restored even if the watermark is damaged. It is also robust to the typical attacks and has ability against tampering over a large area of the image.

Research on Digital Watermarking Algorithm for Anti-geometric Attack

For the problem that the traditional digital watermarking algorithm is less robustness against geometric attacks, this paper introduces the related content of digital watermarking technology, which combs digital watermarking technology, digital watermarking attack technology and digital watermarking evaluation method, and summarizes the improved algorithms proposed in recent years. Next, the traditional wavelet transform algorithm and the improved algorithm based on DCT transform are selected for comparison experiments. The latter combines Arnold scrambling and SVD decomposition, which has better shear resistance. Finally, combined with the research status, the future research focus of digital watermarking algorithm is prospected.

An effective mechanism for medical images authentication using quick response code

Traditional watermarking algorithms suffer from degradations in watermarked image during embedding phase and also bound by differing necessities like embedding capacity, robustness and transparency, these issues can be eliminated using zero watermarking. Zero watermarking facilitates reverse and blind watermark extraction features as it guarantees the integrity of the host image after embedding the watermark image. In this work two methods of zero watermarking algorithms for medical image authentication is proposed, discussions on the two methods one involving singular-value decomposition and the other using composite CT-SVD domain were presented. Experimentations were carried out using medical images. The proposed model best suits for healthcare institutions, as such the proposed scheme is highly resilient and robust against various attacks and facilitates in authenticating the medical images and also present additional information regarding clinical results to the radiologist remotely located. The comparison results show that the proposed method is more robust than further zero watermarking schemes.

A multimodal biometric watermarking system for digital images in redundant discrete wavelet transform

The traditional watermarking algorithms prove the rightful ownership via embedding of independent watermarks like copyright logos, random noise sequences, text etc into the cover images. Coupling biometrics with watermarking evolved as new and secure approach as it embeds user specific biometric traits and thus, narrows down the vulnerability to impostor attacks. A multimodal biometric watermarking system has been proposed in this paper in the redundant discrete wavelet transform(RDWT). Two biometric traits of the user i.e. the iris and facial features are embedded independently into the sub-bands of the RDWT of cover image taking advantage of its translation invariant property and sufficient embedding capacity. The ownership verification accuracy of the proposed system is tested based on the individual biometric traits as well as the fused trait. The accuracy was enhanced while using the fused score for evaluation. The security of the scheme is strengthened with usage of non-linear chaotic maps, randomization via Hessenberg decomposition, Arnold scrambling and multiple secret keys. The robustness of the scheme has been tested against various attacks and the verification accuracy evaluated based on false acceptance rate, false rejection rate, area under curve and equal error rate to validate the efficacy of the proposed scheme.

Geometrically resilient color image zero-watermarking algorithm based on quaternion Exponent moments

Although research on zero-watermarking has made great progress in recent years, most of it has been focused on grayscale images rather than color ones, and cannot resist geometric attacks efficiently. In this paper, we discuss properties of quaternion Exponent moments (QEMs) in detail and propose a robust color image zero-watermarking algorithm which is robust to geometric attacks. We first compute and select robust QEMs of the original color image, and then a binary feature image is constructed using the magnitude of the selected moments. Eventually, a bitwise exclusive-or is applied on the binary feature image and a scrambled binary logo to generate the zero-watermark image. Experimental results show that the proposed zero-watermarking algorithm is robust to both geometric attacks and common image processing attacks effectively. Compared to similar zero-watermarking algorithms and traditional watermarking algorithms based on QEMs, the proposed zero-watermarking algorithm has better performance.

Quality Scalability Aware Watermarking for Visual Content.

Scalable coding-based content adaptation poses serious challenges to traditional watermarking algorithms, which do not consider the scalable coding structure and hence cannot guarantee correct watermark extraction in media consumption chain. In this paper, we propose a novel concept of scalable blind watermarking that ensures more robust watermark extraction at various compression ratios while not effecting the visual quality of host media. The proposed algorithm generates scalable and robust watermarked image code-stream that allows the user to constrain embedding distortion for target content adaptations. The watermarked image code-stream consists of hierarchically nested joint distortion-robustness coding atoms. The code-stream is generated by proposing a new wavelet domain blind watermarking algorithm guided by a quantization based binary tree. The code-stream can be truncated at any distortion-robustness atom to generate the watermarked image with the desired distortion-robustness requirements. A blind extractor is capable of extracting watermark data from the watermarked images. The algorithm is further extended to incorporate a bit-plane discarding-based quantization model used in scalable coding-based content adaptation, e.g., JPEG2000. This improves the robustness against quality scalability of JPEG2000 compression. The simulation results verify the feasibility of the proposed concept, its applications, and its improved robustness against quality scalable content adaptation. Our proposed algorithm also outperforms existing methods showing 35% improvement. In terms of robustness to quality scalable video content adaptation using Motion JPEG2000 and wavelet-based scalable video coding, the proposed method shows major improvement for video watermarking.

Study on an Algorithm for Generating the Multiple Watermark Information using 2D Barcode

In this paper, we propose a multiple watermarking algorithm which embeds an integrated watermark into content using traditional watermarking algorithm. The integrated watermark consists of multiple watermark information and it is useful to trace illegal distribution. The information is generated by using Dot Code A, which can express multiple user information with error correction. An orthogonal transform and code division multiplexing technology are used to spread Dot Code A. This also ensures the algorithm is robust. The embedding range of the AC coefficients is within [-0.5, -0.3] and [0.3, 0.5] in the discrete cosine transform domain. At an embedding strength of 0.7, the signal-to-noise ratio of the test audio is over 53 dB, and we are able to extract the Dot Code A from the watermarked audio exactly.

A Novel Robust Zero-Watermarking Scheme Based on Discrete Wavelet Transform

In traditional watermarking algorithms, the insertion of watermark into the original signal inevitably introduces some perceptible quality degradation. Another problem is the inherent conflict between imperceptibility and robustness. Zero-watermarking technique can solve these problems successfully. But most existing zero-watermarking algorithm for audio and image cannot resist against some signal processing manipulations or malicious attacks. In the paper, a novel audio zero-watermarking scheme based on discrete wavelet transform (DWT) is proposed, which is more efficient and robust. The experiments show that the algorithm is robust against the common audio signal processing operations such as MP3 compression, re-quantization, re-sampling, low-pass filtering, cutting-replacement, additive white Gaussian noise and so on. These results demonstrate that the proposed watermarking method can be a suitable candidate for audio copyright protection.

A new watermarking method based on chaotic mixing and SVD

A new binary watermark embedding method is proposed in this paper based on chaotic mixing and singular value decomposition (SVD) for copyright protection and authenticity. We used the chaotic mixing to mix binary watermark image and SVD transformation to extract the left orthogonal matrix of host image at the same time. Other than traditional watermarking algorithms based on SVD, the binary watermark bits are embedded in the left orthogonal matrix instead of the singular values (SVs) of the host image’s sub-blocks, because the orthogonal matrices contain the texture and detail information of the host image, while the SVs only contain the energy information of host image. This greatly enhances the safety of watermark because the SVs can be easily replaced without much damage to the host image, whereas the orthogonal matrix cannot. Compared with another watermarking method based on modifying the orthogonal matrix, our method maintains the orthogonality of the modified orthogonal matrix. Experimental results showed that our method had higher robustness and was better in resisting normal attacks. The error ratios were reduced by an order of magnitude using the proposed method.

A multipurpose audio aggregation watermarking based on multistage vector quantization

Watermarking technology can achieve multipurpose such as copyright protection, copy protection, and integrity authentication. We propose a novel watermarking approach which involves robust watermark and fragile watermark in a two-stage quantization technique. Traditional watermarking algorithms mostly have poor performance in imperceptibility as the codeword selected from the modified codebook is not optimal. In our method, we select the codeword in the original codebook to ensure optimality. Furthermore, we use Huffman encoding to pick up property which is sensitive to many attacks in the entire aggregation. For copyright protection, the proposed scheme can resist attacks such as lossy compression, noise addition, and normalization. As for content authentication, the proposed scheme is sensitive to various attacks provided by Stirmark Benchmark for Audio. Experimental results show that the proposed method can be used respectively for protecting the copyright and authenticating the integrity of the audio aggregation.

A Robust Zero-Watermarking Algorithm for Audio

In traditional watermarking algorithms, the insertion of watermark into the host signal inevitably introduces some perceptible quality degradation. Another problem is the inherent conflict between imperceptibility and robustness. Zero-watermarking technique can solve these problems successfully. Instead of embedding watermark, the zero-watermarking technique extracts some essential characteristics from the host signal and uses them for watermark detection. However, most of the available zero-watermarking schemes are designed for still image and their robustness is not satisfactory. In this paper, an efficient and robust zero-watermarking technique for audio signal is presented. The multiresolution characteristic of discrete wavelet transform (DWT), the energy compression characteristic of discrete cosine transform (DCT), and the Gaussian noise suppression property of higher-order cumulant are combined to extract essential features from the host audio signal and they are then used for watermark recovery. Simulation results demonstrate the effectiveness of our scheme in terms of inaudibility, detection reliability, and robustness.

Commutative Encryption and Watermarking in Video Compression

A scheme is proposed to implement commutative video encryption and watermarking during advanced video coding process. In H.264/AVC compression, the intra-prediction mode, motion vector difference and discrete cosine transform (DCT) coefficients' signs are encrypted, while DCT coefficients' amplitudes are watermarked adaptively. To avoid that the watermarking operation affects the decryption operation, a traditional watermarking algorithm is modified. The encryption and watermarking operations are commutative. Thus, the watermark can be extracted from the encrypted videos, and the encrypted videos can be re-watermarked. This scheme embeds the watermark without exposing video content's confidentiality, and provides a solution for signal processing in encrypted domain. Additionally, it increases the operation efficiency, since the encrypted video can be watermarked without decryption. These properties make the scheme a good choice for secure media transmission or distribution

Multipurpose image watermarking algorithm based on multistage vector quantization

The rapid growth of digital multimedia and Internet technologies has made copyright protection, copy protection, and integrity verification three important issues in the digital world. To solve these problems, the digital watermarking technique has been presented and widely researched. Traditional watermarking algorithms are mostly based on discrete transform domains, such as the discrete cosine transform, discrete Fourier transform (DFT), and discrete wavelet transform (DWT). Most of these algorithms are good for only one purpose. Recently, some multipurpose digital watermarking methods have been presented, which can achieve the goal of content authentication and copyright protection simultaneously. However, they are based on DWT or DFT. Lately, several robust watermarking schemes based on vector quantization (VQ) have been presented, but they can only be used for copyright protection. In this paper, we present a novel multipurpose digital image watermarking method based on the multistage vector quantizer structure, which can be applied to image authentication and copyright protection. In the proposed method, the semi-fragile watermark and the robust watermark are embedded in different VQ stages using different techniques, and both of them can be extracted without the original image. Simulation results demonstrate the effectiveness of our algorithm in terms of robustness and fragility.