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.

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

This paper considers a scenario in which a source–destination pair needs to establish a confidential connection against an external eavesdropper, aided by the interference generated by another source–destination pair that exchanges public messages. The goal is to compute the maximum achievable secrecy degrees of freedom (S.D.o.F) region of a MIMO two-user wiretap network. First, a cooperative secrecy transmission scheme is proposed, whose feasible set is shown to achieve all S.D.o.F. pairs on the S.D.o.F. region boundary. In this way, the determination of the S.D.o.F. region is reduced to a problem of maximizing the S.D.o.F. pair over the proposed transmission scheme. The maximum achievable S.D.o.F. region boundary points are obtained in closed form, and the construction of the precoding matrices achieving the maximum S.D.o.F. region boundary is provided. The proposed expressions are functions of the number of antennas at each terminal, and apply to any number of antennas, thus constituting an advancement over prior works that have considered only fixed antenna configurations.

Improving Wireless Physical Layer Security via Exploiting Co-Channel Interference

Digital watermarking has been recognized as an effective technique to protect intellectual property by embedding secret information into the digital products. This paper presents a new watermarking technique for digital image applications by using the contourlet domain. The contourlet transform is a powerful tool to capture singularities along smooth object boundaries with different elongated shapes and directions that helps the watermarking technique to achieve high performance. Specifically, the host image is decomposed into subbands by using the contourlet transform. Then, the mid frequency subbands are chosen to embed watermark with suitable embedment factors. The peak signal-to-noise ratio (PSNR) and normalized correlation (NC) are used to evaluate the performance of the algorithm. Simulations on different images are carried out to evaluate the invisibility and robustness of the proposed scheme. The experimental results show that the proposed method outperforms the others in terms of invisibility and robustness for the lossy JPEG compression.

A new image watermarking scheme using contourlet transforms

Digital watermarking is one of the most widely used techniques for the protection of ownership rights of digital audio, images, and videos. One of the desirable properties of a digital watermarking scheme is its robustness against attacks aiming at removing or destroying the watermark from the host data. Different from the common watermarking techniques based on the spatial domain or transform domain, in this paper, a novel scheme of digital image blind watermarking based on the combination of the discrete wavelet transform (DWT) and the convolutional neural network (CNN) is proposed. Firstly, the host images are decomposed by the DWT with 4 levels and, then, the low frequency sub-bands of the first level and the high frequency sub-bands of the fourth level are used as the input data and the output target data to train the CNN model for embedding and extracting the watermark. Experimental results show that the proposed scheme has superior performance against common attacks of JPEG compression, mean and median filtering, salt and pepper noise, Gaussian noise, speckle noise, brightness modification, scaling, cropping, rotation, and shearing operations.

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An Efficient Robust Blind Watermarking Method Based on Convolution Neural Networks in Wavelet Transform Domain

Visual Cryptography Scheme (VCS) is Image Encryption technique Which Generate Share images. An image Steganography is a technique that hide secrete message in image. First selection of image based reCAPTCHA. After that, by applying Visual Cryptography on Black and White (BW) image and generate share1 and share2. In Progressive Visual Cryptography Scheme (PVCS) System share1 hide into reCAPTCHA image (Cover image). For Rotation Scale Transform (RST) based attack we are using transform based domain with Block DWT+SVD transform with modified Zernike Moment for rotational invariant pixel Selection. Also, find out some problems based on Dual Attack with different scheme attacks by the attackers. The easygoing of a powerful assault on the Stego picture by an aggressor is less because of utilization of this Modified Zernike strategy. The primary advantage of the framework is that the picture is moved before installing of the stego picture and de-moved subsequent to inserting.

A study of privacy preserving system based on progressive VCS and RST attacks

The paper proposes an image watermarking algorithm on curvelet transform domain. Different from other conventional methods which embed the watermark in spatial domain, discrete cosine transform (DCT), or discrete wavelet transform (DWT), the present paper uses curvelet transform domain for image watermarking since curvelet transform is effective when representing curves with fewer coefficients than other transforms such as wavelets for the same accuracy. The paper will investigate the different scales of curvelet transform domain for embedding the watermark to achieve both invisibility and robustness. The performance of image watermarking in curvelet transform domain is compared with the same algorithm but applied on DCT-DWT combined domain. Peak signal-to-noise ratio (PSNR) and normalized correlation (NC) are used to evaluate the invisibility and the robustness of the algorithms, respectively. Experimental results show that invisibility and robustness are ensured. Performance in terms of invisibility and robustness of the proposed algorithm is better than that applying on DCT-DWT combined domain for the lossy JPEG compression attacks, speckle and Gaussian noise.

An improved image watermarking scheme using selective curvelet scales

In this paper, we propose two secure multiuser multiple-input multiple-output transmission approaches based on interference alignment (IA) in the presence of an eavesdropper. To deal with the information leakage to the eavesdropper as well as the interference signals from undesired transmitters (Txs) at desired receivers (Rxs), our approaches aim to design the transmit precoding and receive subspace matrices to minimize both the total inter-main-link interference and the wiretapped signals (WSs). The first proposed IA scheme focuses on aligning the WSs into proper subspaces while the second one imposes a new structure on the precoding matrices to force the WSs to zero. When the channel state information is perfectly known at all Txs, in each proposed IA scheme, the precoding matrices at Txs and the receive subspaces at Rxs or the eavesdropper are alternatively selected to minimize the cost function of an convex optimization problem for every iteration. We provide the feasible conditions and the proofs of convergence for both IA approaches. The simulation results indicate that our two IA approaches outperform the conventional IA algorithm in terms of average secrecy sum rate.

On the Interference Alignment Designs for Secure Multiuser MIMO Systems

This paper is concerned with the digital image watermarking techniques to protect intellectual property and to authenticate digital images. Different from the most conventional methods using the discrete cosine transforms (DCT) and discrete-wavelet transforms (DWTs), this paper exploits the improved Laplacian pyramid transform to develop a new image watermarking scheme in which the improved Laplacian pyramid transform is used to decompose and reconstruct the host image. Then, to select an appropriate watermarking solution, we investigate the various frequency sub-band regions with different the levels and strength factors to perform the watermark embedding. Finally, we conduct experiments to investigate the invisibility and robustness of the proposed algorithm in terms the peak signal-to-noise ratio (PSNR), normalized correlation (NC), and structural similarity index (SSIM). Experimental results showed that our proposed scheme offers good robustness and invisibility. As compared to the watermarking schemes using the curvelets, our watermarking scheme is more robust for the lossy JPEG compression and Gaussian low pass filtering attacks. In addition, our method is also efficient in terms of computational time.

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Kha Hoang Ha

Papers

An improved image watermarking scheme using selective curvelet scales

A new image watermarking scheme using contourlet transforms

On the Interference Alignment Designs for Secure Multiuser MIMO Systems

A Robust Image Watermarking Scheme Based on the Laplacian Pyramid Transform

On the Interference Alignment Designs for Secure Multiuser MIMO Systems