A self recoverable dual watermarking scheme for copyright protection and integrity verification

Dual watermarking implies embedding of robust as well as fragile watermarks into the same cover image. It facilitates integration of copyright protection and integrity verification into the same scheme. However, most of such existing state of art approaches either lacked the feature of tamper detection and original content recovery or provided an approximation using coarser block level approach. The proposed self recoverable dual watermarking scheme integrates all the aforementioned functionalities of copyright protection, tamper detection and recovery into one scheme. The scheme is independent of the order of embedding of robust and fragile watermarks as these are embedded in different regions of the cover image. It performs tamper detection and recovery, both at the pixel level. The scheme obtains recovery information for each 2×2 image block in just eight bits which are further encoded to only four bits via mapping table. This reduction in recovery bits allows efficient embedding of copyright information which is tested against comprehensive set of attacks. The scheme is found to be robust against noises, filtering, histogram equalization, rotation, jpeg compression, motion blur etc. Besides the normalized cross correlation value, the evaluation of the extracted copyright information is also being done using various objective error metrics based on mutual relation between pixels, their values and locations respectively. The imperceptibility and visual quality of the watermarked as well as recovered image is found to be satisfactorily high. Three major categories of images: natural, texture as well as satellite have been tested in the proposed scheme. Even minute alterations can be chalked out as the detection accuracy rate has been enumerated on pixel basis. The scheme can tolerate tampering ratios upto 50 percent though the visual quality of the recovered image deteriorates with increasing tampering ratio. Comparative results based on normalized cross correlation, probability of false acceptance, probability of false rejection and peak signal to noise ratio metrics validate the efficacy of the proposed scheme over other existing state of art approaches.     

RDWT domain statistical watermark detector using FRHFMs magnitudes and bivariate Cauchy-Rayleigh distribution

Imperceptibility, robustness and data payload, which are complimentary to each other, are widely considered as the three main properties vital for any image watermarking systems. It is a challenging work to design a statistical model-based multiplicative watermarking scheme for achieving the tradeoff among three main properties. In this paper, we propose a novel statistical image watermarking scheme by modeling local redundant discrete wavelet transform (RDWT) and fast Radial harmonic Fourier moments (FRHFMs) magnitudes with bivariate Cauchy-Rayleigh distribution. Our image watermarking scheme consists of two parts, namely, embedding and detection. In the embedding process, RDWT is firstly performed on the host image and RDWT highpass subbands are divided into non-overlapping blocks. Then FRHFMs are computed on RDWT coefficient blocks. And finally, the watermark signal is inserted into robust RDWT-FRHFMs magnitudes through a non-linear multiplicative approach. In the detection process, robust local RDWT-FRHFMs magnitudes are firstly modeled by employing bivariate Cauchy-Rayleigh distribution, which can capture accurately both marginal distributions and strong dependencies of local RDWT-FRHFMs magnitudes. Statistical model parameters are then estimated effectively by the method of logarithmic cumulants (MoLC) approach. And finally, an image watermark detector for multiplicative watermarking is developed using bivariate Cauchy-Rayleigh model and locally most powerful (LMP) test. Also, we utilize the bivariate Cauchy-Rayleigh model to derive the closed-form expressions for the watermark detector. After performance testing and comparison with the experimental results of existing methods, the proposed statistical image watermarking method has achieved relatively ideal results in terms of robustness, imperceptibility and data payload.

     

An adaptive color image watermarking using RDWT-SVD and artificial bee colony based quality metric strength factor optimization

Image watermarking has emerged as a useful method for solving security issues like authenticity, copyright protection and rightful ownership of digital data. Existing watermarking schemes use either a binary or grayscale image as a watermark. This paper proposes a new robust and adaptive watermarking scheme in which both the host and watermark are the color images of the same size and dimension. The security of the proposed watermarking scheme is enhanced by scrambling both color host and watermark images using Arnold chaotic map. The host image is decomposed by redundant discrete wavelet transform (RDWT) into four sub-bands of the same dimension, and then approximate sub-band undergoes singular value decomposition (SVD) to obtain the principal component (PC). The scrambled watermark is then directly inserted into a principal component of scrambled host image, using an artificial bee colony optimized adaptive multi-scaling factor, obtained by considering both the host and watermark image perceptual quality to overcome the tradeoff between imperceptibility and robustness of the watermarked image. The hybridization of RDWT-SVD provides an advantage of no shift-invariant to achieve higher embedding capacity in the host image and preserving the imperceptibility and robustness by exploiting SVD properties. To measure the imperceptibility and robustness of the proposed scheme, both qualitative and quantitative evaluation parameters like peak signal to noise ratio (PSNR), structural similarity index metric (SSIM) and normalized cross-correlation (NC) are used. Experiments are performed against several image processing attacks and the results are analyzed and compared with other related existing watermarking schemes which clearly depict the usefulness of the proposed scheme. At the same time, the proposed scheme overcomes the major security problem of false positive error (FPE) that mostly occurs in existing SVD based watermarking schemes.     

Hiding biometric data

With the wide spread utilization of biometric identification systems, establishing the authenticity of biometric data itself has emerged as an important research issue. The fact that biometric data is not replaceable and is not secret, combined with the existence of several types of attacks that are possible in a biometric system, make the issue of security/integrity of biometric data extremely critical. We introduce two applications of an amplitude modulation-based watermarking method, in which we hide a user's biometric data in a variety of images. This method has the ability to increase the security of both the hidden biometric data (e.g., eigen-face coefficients) and host images (e.g., fingerprints). Image adaptive data embedding methods used in our scheme lead to low visibility of the embedded signal. Feature analysis of host images guarantees high verification accuracy on watermarked (e.g., fingerprint) images.     

Adaptive and blind watermarking scheme based on optimal SVD blocks selection

To protect the ownership of the digital products, a novel adaptive and blind watermarking scheme is designed. Firstly, the underlying reason of image quality degradation in singular value decomposition (SVD)-based watermarking scheme is analyzed and the potential scenario causing visible destroy is pointed out. Then the optimal SVD blocks selection strategy is proposed to improve the imperceptibility. Different from other block selection rules devised by subjective evaluation means, our selection rule aims to retain the image quality as much as possible from the source. Furthermore, information entropy is utilized to achieve the purpose of adaptive embedding. In the experiment, the proposed watermarking scheme is tested under several attacks, such as noise attack, JPEG compression, blurring, sharping, and etc. Finally, the proposed watermarking scheme is compared with other existing schemes, and the experimental results demonstrate the robustness, imperceptibility and superior of the proposed watermarking scheme.

     

Chaotic based secure watermarking approach for medical images

In this paper, a chaotic based secure medical image watermarking approach is proposed. The method is using non sub-sampled contourlet transform (NSCT), redundant discrete wavelet transform (RDWT) and singular value decomposition (SVD) to provide significant improvement in imperceptibility and robustness. Further, security of the approach is ensured by applying 2-D logistic map based chaotic encryption on watermarked medical image. In our approach, the cover image is initially divided into sub-images and NSCT is applied on the sub-image having maximum entropy. Subsequently, RDWT is applied to NSCT image and the singular vector of the RDWT coefficient is calculated. Similar procedure is followed for both watermark images. The singular value of both watermarks is embedded into the singular matrix of the cover. Experimental evaluation shows when the approach is subjected to attacks, using combination of NSCT, RDWT, SVD and chaotic encryption it makes the approach robust, imperceptible, secure and suitable for medical applications.

     

Rightful ownership through image adaptive DWT-SVD watermarking algorithm and perceptual tweaking

In this paper, a tailored blended image adaptive watermarking scheme has been presented, which is based on DWT and SVD. Through this paper an attempt has been made to solve the problem of false positive while maintaining the robustness and imperceptibility with the help of principal component and perceptual tuning of the image. Perceptual tuning is a non-blind technique and based on the objective quality of image. The embedding strength is made dependent on watermark features as well as of host in wavelet domain by using tuning parameter which is user specific. The idea of embedding the principal component of intermediate frequency sub-bands of watermark image into singular values of perceptually tuned intermediate frequency sub-bands of host image have been exploited. The proposed algorithm is providing the adaptive behavior towards the image content for perceptual transparency and at the same time avoiding the possibility of false watermark extraction well supported by a private key, which is necessary at the time of extraction. Thus the proposed watermarking algorithm is a kind of non-blind, image adaptive and suitable for rightful ownership. Various comparative results make the algorithm superior in terms of intentional and non-intentional attacks. Also the algorithm is strong against the print and scan attack.     

基于黑盒水印的NLP神经网络版权保护

随着自然语言处理（NLP，natural language processing）技术的快速发展，语言模型在文本分类和情感分析中的应用不断增加。然而，语言模型容易遭到盗版再分发，对模型所有者的知识产权造成严重威胁。因此，研究者着手设计保护机制来识别语言模型的版权信息。现有的适用于文本分类任务的语言模型水印无法与所有者身份相关联，且鲁棒性不足以及无法再生成触发集。为了解决这些问题，提出一种新的适用于文本分类任务模型的黑盒水印方案，可以远程快速验证模型所有权。将模型所有者的版权消息和密钥通过密钥相关的哈希运算消息认证码（HMAC，hash-based message authentication code）得到版权消息摘要，由HMAC得到的消息摘要可以防止被伪造，具有很强的安全性。从原始训练集各个类别中随机挑选一定的文本数据，将摘要与文本数据结合构建触发集，并在训练过程中对语言模型嵌入水印。为了评估水印的性能，在IMDB电影评论、CNEWS中文新闻文本分类数据集上对3种常见的语言模型嵌入水印。实验结果表明，在不影响原始模型测试精度的情况下，所提出的水印验证方案的准确率可以达到 100%。即使在模型微调和剪枝等常见攻击下，也能表现出较强的鲁棒性，并且具有抗伪造攻击的能力。同时，水印的嵌入不会影响模型的收敛时间，具有较高的嵌入效率。     

鲁棒视频水印研究进展

数字视频在当前通信世界中被认为是一种重要而有效的媒体,广泛应用于新闻、短视频和有线网络广播视频节目中。随着计算机与互联网技术的发展,数字视频内容容易被侵权使用者肆意复制和传播,如何保护视频版权日益成为人们关注的问题。鲁棒视频水印是实现视频版权保护的一种有效手段。作为数字视频水印的分支,鲁棒视频水印是一种通过特定算法在需要被保护的视频对象中嵌入秘密信息——水印来证明版权归属的技术。本文对当前的视频水印技术进行了概述,对视频水印的概念、应用场景、分类方式、设计要求、发展历程和相关经典方法进行了介绍和梳理。本文归纳总结了2016—2021年鲁棒视频水印相关研究工作,包括基于内容的、基于码流的、基于深度学习和其他类型视频水印,并对其中部分工作进行了相应的性能比较和分析。其中,基于内容的视频水印方法将视频看做帧序列,由于在每一帧上应用水印算法,不考虑视频的编解码过程,这类方法实现简单,计算效率高;基于码流的视频水印方法将水印嵌入到编码比特流中,该方案更快速,故可支持实时视频水印应用;基于深度学习的方法取代了依靠手工设计的特征来提高水印的性能。最后分析了鲁棒视频水印的未来发展趋势。     

Multi-instance cancellable biometrics schemes based on generative adversarial network

The main role of cancellable biometric schemes is to protect the privacy of the enrolled users. The protected biometric data are generated by applying a parametrized transformation function to the original biometric data. Although cancellable biometric schemes achieve high security levels, they may degrade the recognition accuracy. One of the mostwidely used approaches to enhance the recognition accuracy in biometric systems is to combine several instances of the same biometric modality. In this paper, two multi-instance cancellable biometric schemes based on iris traits are presented. The iris biometric trait is used in both schemes because of the reliability and stability of iris traits compared to the other biometric traits. A generative adversarial network (GAN) is used as a transformation function for the biometric features. The first scheme is based on a pre-transformation feature-level fusion, where the binary features of multiple instances are concatenated and inputted to the transformation phase. On the other hand, the second scheme is based on a post-transformation feature-level fusion, where each instance is separately inputted to the transformation phase. Experiments conducted on the CASIA Iris-V3-Internal database confirm the high recognition accuracy of the two proposed schemes. Moreover, the security of the proposed schemes is analyzed, and their robustness against two well-known types of attacks is proven.

     

Securing Fingerprint Images Using PSO-Based Wavelet Domain Watermarking

ABSTRACT

Watermarking techniques are used in biometric systems for the purpose of protecting and authenticating biometric data. This paper presents an efficient scheme to protect and authenticate fingerprint images by watermarking with their corresponding facial images in the wavelet domain using Particle Swarm Optimization (PSO). The key idea is to use PSO to find the best discrete wavelet transform (DWT) coefficients where the facial image data can be embedded. The objective function for PSO is based on the fingerprint image quality with respect to the Structural Similarity index (SSIM) and Orientation Certainty Level index (OCL). As a result, embedding the facial image data in the selected coefficients generated by the proposed method not only results in minimum distortion of the host image but also retains the feature set of the original fingerprint to be used in fingerprint recognition. The robustness of the watermark extracted using the proposed technique has been tested against various image processing attacks. This concept of watermarking a biometric image with another biometric image finds application in multimodal biometric authentication for a more secure system of personal recognition at the receiver's end.     

Multiresolution fragile watermarking using complex chirp signals for content authentication

This paper proposes a wavelet-domain multiresolution fragile watermarking scheme using an improved quantization-index-modulation (QIM) embedding technique. A secure embedding zone is exploited in our proposed scheme to reduce the false detection rate of Kundur's scheme. The frequency modulated (FM) complex chirp signal is employed as watermark. Both the real and the imaginary parts of the chirp signal are embedded simultaneously in a hierarchical manner. Unlike the conventional schemes, the proposed scheme does not require the original watermark for content integrity verification and quality assessment for the distorted watermarked content. The blind authentication process allows embedding of arbitrary FM chirp watermarks.     

Tamper detection and self-recovery of biometric images using salient region-based authentication watermarking scheme

Biometric images can be split into regions of salient (ROI) and regions of background (ROB) based on salient region detection. During the process of watermark embedding, salient regions which contain rich-information are less affected by the watermark, therefore can be embedded into more watermarks, and regions of background (ROB) are susceptible to the effect of watermarks, so that they should be embedded lighter or even none in order to preserve the recognition quality of biometric images. In this paper, a novel scheme for tamper detection and self-recovery of biometric images using salient region-based authentication watermarking is proposed. Firstly, we propose a novel multi-level authentication watermarking scheme, which is used to verify the integrity of biometric images. Secondly, biometric data of these biometric images which is used as information watermarks is embedded into themselves. As a result, verification systems can recover the damaged data of original biometric images with hidden information based on tampering detection result. Experimental results and theoretic analysis show that our proposed scheme can detect tampered regions, and recover biometric data while keeping the recognition quality.     

A new robust and secure digital image watermarking scheme based on the integer wavelet transform and singular value decomposition

In this paper, a new robust and secure digital image watermarking scheme that can be used for copyright protection is proposed. The scheme uses the integer wavelet transform (IWT) and singular value decomposition (SVD). The grey image watermark pixels values are embedded directly into the singular values of the 1-level IWT decomposed sub-bands. Experimental results demonstrate the effectiveness of the proposed scheme in terms of robustness, imperceptibility and capacity due to the IWT and SVD properties. A challenge due to the false positive problem which may be faced by most of SVD-based watermarking schemes has been solved in this work by adopting a digital signature into the watermarked image. The proposed digital signature mechanism is applied to generate and embed a digital signature after embedding the watermarks; the ownership is then authenticated before extracting watermarks. Thus, the proposed scheme achieved the security issue where the false positive problem is solved, in addition to that, the scheme is considered as a blind scheme. A computer simulation is used to verify the feasibility of the proposed scheme and its robustness against various types of attacks and to compare it with some previous schemes. Furthermore, the statistical Wilcoxon signed rank test is employed to certify the effectiveness of the proposed scheme.     

An efficient fragile watermarking scheme with multilevel tamper detection and recovery based on dynamic domain selection

Self-recoverable fragile watermarking is meant for accurate tamper localization as well as image recovery with superior visual quality. However, most of the existing state of art approaches perform authentication and recovery on block basis owing to which the entire block is categorized as tampered in case of alteration of one or more pixels of it. This, results in staircase formation of tamper detected regions, hence lacking in accuracy. Furthermore, the visual quality of the recovered image also deteriorates as an approximate value is assigned to all the block pixels corresponding to the altered region. The proposed watermarking scheme performs both authentication and recovery pixelwise. The authentication of each pixel is done via multi level tamper detection(MLTD) through three authentication bits based on value, location and neighbourhood information. The domain for image recovery is chosen dynamically based on the content of the block, may it be in spatial domain for smooth blocks or frequency domain for the rough ones. This provides high accuracy in recovery. As the embedding of recovery information is done in the frequency domain, the imperceptibility of the watermarked image scheme remains high. Also, embedding of authentication information in the spatial domain maintains its fragile nature. Even for higher tampering ratios, the lost content is rebuilt with high peak signal to noise ratio(PSNR) of the recovered image. The probabilities of false rejection and false acceptance head towards the ideal value for most of the empirical analysis. Comparative study via metric evaluation of probability of false rejection (PFR), probability of false acceptance (PFA) and PSNR of recovered image for different standard test cover images demonstrate the efficacy of the proposed scheme over other existing state of art approaches. Further, the security of the proposed scheme remains high due to usage of multi-layered secret keys and chaos based random mapping handling worst tamper scenarios.     

A new digital image watermarking scheme based on Schur decomposition

In this paper, we present a new digital watermarking scheme for ownership protection. The algorithm embeds the watermark in the Schur decomposition components of the cover image. We also show that this algorithm is noninvertible. Comparisons with other algorithms indicate that the proposed algorithm is robust against most common attacks including geometrical distortions and jpeg compression attacks. Simulations show that the performance of this algorithm outperforms the closely related singular value decomposition based algorithms. More specifically, the proposed algorithm is more robust and requires less number of computations. In addition, our algorithm does not suffer the false positive detection problem inherent in SVD based algorithms.     

A semi-oblivious energy-aware adaptive watermarking for wireless image sensor networks

In this paper, we propose a semi-oblivious energy-aware adaptive watermarking scheme for wireless image sensor networks, which considered key characteristics such as the embedding capacity, security, imperceptibility, computation, and communication energy requirements. We evaluated the distortion in cover image due to watermark redundancies, the number of embedding locations with respect to two channel adaptive parameters, and the impact of compression of cover image on the correctness of extracted watermark. In addition, we investigated the robustness of the scheme against statistical analysis attacks. The results have shown that the proposed scheme has sufficient capacity to embed redundant watermarks in the cover image in an imperceptible manner with reasonably low distortion. The scheme is also considered relatively robust against collusion and middleman attacks.     

Contourlet-based image and video watermarking robust to geometric attacks and compressions

In this paper, we first propose a new blind image watermarking scheme robust to geometric attacks and compressions. The scheme is based on contourlet transform (CT) and principal component analysis (PCA). The scheme uses the principal components of the largest contourlet coefficients of the last directional subband of the cover image to embed the watermark. Meanwhile, with the noise visibility function (NVF), the watermarking strength is adjusted adaptively to preserve the perceptual quality of the image. The watermark can be detected with high accuracy after various possible distortions. The normalized correlation (NC) between the original watermark and the watermark extracted from the distorted watermarked image is used as the robustness evaluation criterion. The simulation results demonstrate that the proposed scheme has good performance in terms of both quality and robustness against a variety of image-processing attacks, such as rotation, scaling and image compressions. Then we extend the scheme to blind video watermarking. The performance of the video watermarking scheme is evaluated against video attacks like rotation, frame averaging, noise additions and video compressions. The introduction of the CT produces robustness against image and video compressions, and the PCA yields resistance to geometric attacks.

     

A low-cost method for reliable ownership identification of medical images using SVM and Lagrange duality

Prevention of false positive and false negative errors is a major challenge for ownership identification and proof of ownership applications using digital image watermarking. Such errors are more critical with sensitive data, such as electronic patient records (EPRs) in medical image watermarking. A false positive error is a watermark detection error, which means that a watermark is detected in a media where there is no watermark. In contrast, a false negative error is an inability of the watermark detector to detect an embedded watermark in a watermarked image. These errors make ownership assessments unreliable, and the incorrect ownership identification of a patient’s record could result in failure of the correct diagnostics and treatments. To address this type of problem, a low-cost technique based on a support vector machine (SVM) and Lagrange duality was proposed to achieve reliable approximations for ownership identification in medical image watermarking without requiring the correction of attacked watermarked images. In this technique, the results of the ownership evaluation are categorized into two independent classes, namely watermark-detected and watermark-not-detected, and higher geometric margins between these classes are associated with higher reliability. To address additional situations with false positive and false negative errors, four different situations, including watermarked, unwatermarked, attacked watermarked and attacked unwatermarked images, were investigated. Experiments were conducted on duo-ISB-bit-plane (BiISB) watermarking using the histogram intersection (HI) technique as a testing platform under JPEG2000 and JPEG image compression attacks and using two groups of images: standard image processing images and X-ray medical images. The experimental investigations revealed that the HI technique guarantees that the rightful owner can be reliably identified even after severe attacks and in the face of context similarities between the watermark and the embedding pixels of the host image.     

一种新的JPEG图像认证半脆弱水印算法

提出了一种用于JPEG图像认证的半脆弱数字水印算法,它根据JPEG图像压缩过程中的DCT系数的不变性原理进行水印生成和嵌入调制,并结合一种有效的算法隐性地考虑到所有非零DCT系数的符号、大小关系,在未增加水印信息嵌入强度的情况下,实现了图像应对变换域攻击的更有效保护。同时,在检测算法中加入对虚警区的判断,增加了对窜改区域定位的准确性。实验表明,该算法实现的水印有很好的视觉透明度,有效的承受JPEG压缩,同时对其他恶意篡改敏感并能够准确定位篡改位置。