Feature point-based 3D mesh watermarking that withstands the cropping attack

Robust Video watermarking techniques based on DPCM Encoder and permutated DCT spectrum combined with QIM is introduced. For this purpose the pixels of incoming frames undergo permutation, followed by block wise DCT transform. The DPCM encoder generates differential spectral images. The significant coefficients of these differential spectral images are selected for embedding procedure by quantization index modulation (QIM) method. By this technique the watermark is more robust against attacks and compression. To further increase robustness and to avoid visible degradation additionally the frame order and the watermark pixels were rearranged. To extract the watermark from the video the same operations have to be done on the decoder side. The incoming video frames are permutated followed by block wise DCT transform. After the decoder builds the differential spectral image the embedded coefficients can be selected and watermark extracted by inverse QIM.

Copyright notification and enforcement, authentication, covert communication, and hybrid transmission applications such as digital audio broadcasting are examples of emerging multimedia applications for digital watermarking and information embedding methods, methods for embedding one signal (e.g., the digital watermark) within another "host" signal to form a third, "composite" signal. The embedding is designed to achieve efficient trade-offs among the three conflicting goals of maximizing information-embedding rate, minimizing distortion between the host signal and composite signal, and maximizing the robustness of the embedding. We present a class of embedding methods called quantization index modulation (QIM) that achieve provably good rate-distortion-robustness performance. These methods, and low-complexity realizations of them called dither modulation, are provably better than both previously proposed linear methods of spread spectrum and nonlinear methods of low-bit(s) modulation against square-error distortion-constrained intentional attacks. We also derive information-embedding capacities for the case of a colored Gaussian host signal and additive colored Gaussian noise attacks. These results imply an information embedding capacity of about 1/3 b/s of embedded digital rate for every Hertz of host signal bandwidth and every dB drop in received host signal quality. We show that QIM methods achieve performance within 1.6 dB of capacity, and we introduce a form of postprocessing we refer to as distortion compensation that, when combined with QIM, allows capacity to be achieved. In addition, we show that distortion-compensated QIM is an optimal embedding strategy against some important classes of intentional attacks as well. Finally, we report simulation results that demonstrate the performance of dither modulation realizations that can be implemented with only a few adders and scalar quantizers.

This paper proposes an active steganalysis method for quantization index modulation (QIM)-based steganography. The proposed nonparametric steganalysis method uses irregularity (or randomness) in the test image to distinguish between the cover image and the stego image. We have shown that plain quantization (quantization without message embedding) induces regularity in the resulting quantized object, whereas message embedding using QIM increases irregularity in the resulting QIM-stego. Approximate entropy, an algorithmic entropy measure, is used to quantify irregularity in the test image. The QIM-stego image is then analyzed to estimate secret message length. To this end, the QIM codebook is estimated from the QIM-stego image using first-order statistics of the image coefficients in the embedding domain. The estimated codebook is then used to estimate secret message. Simulation results show that the proposed scheme can successfully estimate the hidden message from the QIM-stego with very low decoding error probability. For a given cover object the decoding error probability depends on embedding rate and decreases monotonically, approaching zero as the embedding rate approaches one.

In this paper, we present a new robust database watermarking scheme the originality of which stands on a semantic control of the data distortion and on the extension of quantization index modulation (QIM) to circular histograms of numerical attributes. The semantic distortion control of the embedding process we propose relies on the identification of existing semantic links in between values of attributes in a tuple by means of an ontology. By doing so, we avoid incoherent or very rare record occurrences which may bias data interpretation or betray the presence of the watermark. In a second time, we adapt QIM to database watermarking. Watermark embedding is conducted by modulating the relative angular position of the circular histogram center of mass of one numerical attribute. We theoretically demonstrate the robustness performance of our scheme against most common attacks (i.e., tuple insertion and deletion). This makes it suitable for copyright protection, owner identification, or traitor tracing purposes. We further verify experimentally these theoretical limits within the framework of a medical database of more than one half million of inpatient hospital stay records. Under the assumption imposed by the central limit theorem, experimental results fit the theory. We also compare our approach with two efficient schemes so as to prove its benefits.

Rapid development of the digital technology and internet has made copyright protection and ownership verification of digital audio data hot research topics that have attracted a lot of interest from different parties. Since the traditional audio protection algorithms cannot solve all the problems of audio copyright protection and digital right management (DRM) due to the unique audio data features and algorithm limitations, this thesis is proposed to address the issue of audio copyright protection using watermarking techniques. Firstly, a new perception-based watermarking scheme for MPEG-4 scalable to lossless (SLS) audio is proposed. Under the control of the psychoacoustic model, the significant part of integer modified discrete cosine transform (IntMDCT) coefficients are adaptively modified during MPEG-4 SLS audio compression taking robustness, imperceptibility and security into consideration. The chaotic watermark generated by chaos is then embedded to ensure security. Moreover, the adaptive spread spectrum (SS) method is exploited to further optimize the tradeoff between robustness and transparency of this scheme. Secondly, a blind and robust audio watermarking scheme based on singular value decomposition (SVD) – followed by discrete cosine transform (DCT) with the synchronization code technique is proposed. A binary watermark is embedded into the high frequency band of the SVD-DCT block. Chaotic sequence is adopted as the synchronization code and inserted into the host signal. Thirdly, a new and robust audio watermarking scheme based on lifting wavelet transform (LWT) and SVD is proposed. Specifically, the watermark data is efficiently inserted in the low coefficient of the frequency subband of LWT audio taking advantage of both SVD and quantization index modulation (QIM). Furthermore, the synchronization code technique is also integrated in the hybrid LWT-SVD audio watermarking method. Finally, a particle swarm optimization (PSO) and SVD based audio watermarking scheme is proposed. The watermark is embedded by modifying singular values (SVs) of the host audio signal with the SS method. The designed optimization technique employs PSO to search for the optimal watermark strength by continuously adjusting the fitness values so that the conflicting requirements of robustness and imperceptibility of the watermark are satisfied optimally. Moreover, the proposed scheme has the flexibility to include or remove various watermarking attacks during training for optimization. The experimental results validate the practicality of the proposed methods and show that the proposed algorithms are very robust to typical signal manipulations. Furthermore, the results of comparison with other similar state-of-the-art audio watermarking techniques indicate that the proposed algorithms are more robust against most common signal processing attacks while preserving good imperceptibility.

The mainstream adaptive steganography algorithm is difficult to resist scaling attack, and the anti-detection performance of the algorithm based on quantization index modulation is not high enough. To solve the above problems, this paper proposes a spatial image adaptive steganography algorithm based on Zernike moment to resist scaling attack and statistic detection. First, the Zernike moment of the normalized cover image is extracted and the new cover is obtained by the dither modulation algorithm. Second, the minimized distortion embedding is realized by Spatial UNIversal WAvelet Relative Distortion (S-UNIWARD) and syndrome-trellis codes coded. And finally, the stego image is generated by changing the original Zernike moment according to the modified amplitude of the new cover. The experimental results show that the proposed algorithm is robust to the three common scaling attacks, and the message extraction error rate is significantly lower than the S-UNIWARD steganography after the scaling attacks; moreover, compared with the steganography algorithm based on quantization index modulation, the proposed algorithm has higher detection resistance.

We propose a system in which the watermark message is embedded into audio signal by means of Quantization Index Modulation (QIM) scheme. However, the method is sensitive to gain scaling attack. We use a value-metric scaling invariant method called Rational Dither Modulation (RDM) to cope with this problem. At the same time, we exploit the psychoacoustic model to improve the audio signal's perceptual quality after the watermark embedding procedure. In comparison of the traditional QIM which use a fixed quantization step, our method adjusts the quantization step with psychoacoustic model adaptively. Experimental results show that our watermarking scheme is robust against common signal processing attacks while keeping the watermarked audio a high perceptual quality.

With the development of digital technology, there are many problems in voice protection and authorization. As a solution, digital watermarking can solve these problems. The principle of this method is to detect tampering by embedding the watermark in the original signal. In this paper, a speech watermarking method based on Quantization Index Modulation(QIM) and double Discrete Cosine Transform(DDCT) is proposed. Firstly, the original signal is segmented into frames and DCT is applied to all these frames. The AC coefficients which contain the details of the signal are chosen for DCT again to reduce the distortions caused by watermarking. The QIM technique is employed for embedding watermarks into the AC coefficients after the DDCT, and we select the most appropriate quantization step so that the modifications of signal will not cause serious distortion in speech quality. Each AC coefficient of one frame is embedded with one-bit watermark, and the majority voting is used to extract the watermark for better robustness. In terms of robustness and fragility, we evaluate the proposed approach. The experimental results show that the proposed method can not only provide satisfactory robustness and tamper resistance to signal processing, but also meet the requirements of non audible knowledge.

Transcoding resilient video watermarking scheme based on spatio-temporal HVS and DCT

Digital watermarking consists in embedding imperceptible information into a host signal. It has been proposed to solve problems as varied as the protection of the copyright, content authentication, fingerprinting and broadcast monitoring. This paper presents a new approach for audio watermarking using the QR factorization in wavelet domain. This approach is based on embedding a watermark binary image in the R matrices of low frequency blocks DWT coefficients of audio signal. In this algorithm, the watermark is embedded by applying a Quantization Index Modulation (QIM) process on the determined optimal sample for each matrix R. The watermark can be blindly extracted without the knowledge of the original audio signal. Experimental results show that the proposed audio watermarking scheme maintains high quality of the audio signal. Signal to Noise Ratio (SNR), Log Spectral Distortion (LSD) and Mean Opinion Score (MOS) are about 40 dB, 0.37 dB and 4.84, respectively. Moreover, the scheme is quite robust against common signal processing attacks such as noise addition, filtering and MP3 compression. In addition, this method ensures a secure extraction process by using a private key, making it suitable for secure applications such as copyright protection.

We present a general method to improve watermark robustness by exploiting the masking effect of surface roughness on watermark visibility, which, to the best of our knowledge, has not been studied in 3D digital watermarking. Our idea is to adapt watermark strength to local surface roughness based on the knowledge that human eyes are less sensitive to changes on a rougher surface patch than those on a smoother surface. We implemented our idea in a modified version of a well known method proposed by Benedens [3]. As an additional contribution, we modified Benedens's method in two ways to improve its performance. The first improvement led to a blind version of Benedens's method that no longer requires any key that depends on the surface mesh of the cover 3D object. The second improvement concerned the robustness of bit `1' in the watermark. Experimental results showed that our new method permits to improve watermark robustness by 41% to 56% as compared to the original Benedens's method. Further analyses indicated that the average watermark strength by our roughness-adaptive method was larger than that by the original Benedens's method while ensuring watermark imperceptibility. This was the main reason for the improvement in robustness observed in our experiments. We conclude that exploiting the masking property of human vision is a viable way to improve the robustness of 3D watermarks in general, and therefore could be applied to other 3D digital watermarking techniques.

In this paper, a new robust and secure video watermarking scheme based on discrete Wavelet Transform (DWT), singular value decomposition (SVD), and Laplacian pyramid is proposed for copyright protection applications. The main contributions of this work are: 1) Increasing watermark robustness towards common signal processing attacks by separating the watermark image into a high-frequency image and a low-frequency image using laplacian pyramid. Then, the singular values of each of the low-frequency watermark image and the high-frequency watermark image are hidden in two different DWT subbands of the original video frame. Separating the watermark and hiding its two parts in two different subbands of the DWT of the video frame makes it robust towards noise, filtering, and compression attacks. 2) Improving the quality of the extracted watermarks via correcting the received watermarked videos using SURF points when those videos are geometrically attacked, mainly by rotation, scaling, and shear attacks. 3) Increasing security and avoiding false positive problems (FPP) associated with SVD by using perceptual image hashing in the proposed scheme. Through experimental results and comparisons to other techniques, the proposed scheme has shown very high imperceptibility for the tested watermarked videos in terms of peak signal to noise ratio (PSNR). Also, the proposed scheme has demonstrated high watermark robustness towards various types of attacks, and an improvement in the quality of the extracted watermarks from 4 to 20 dB compared to other techniques.

Multiple digital watermarking is an important and challenging task in geographic information science and data security. Vector geographic data are a basic data format for digital geographic data storage, and the security protection of these data involves copyright protection and tracking. As part of the solution, existing digital watermarking algorithms have made contributions to vector geographic data protection. However, when vector geographic data flow through multiple units, they need to be marked to ensure that the original data are not destroyed during data processing. Existing single or multiple data watermarking algorithms often fail in the presence of data processing because the new watermarks overlay the old ones. Consequently, a multiple digital watermarking algorithm based on multiple QIM (quantization index modulation) is proposed. First, based on traditional quantization index modulation (QIM), a multiple QIM is proposed. Unlike traditional QIM, in multiple QIM, the process of quantization is executed multiple times depending on the number of watermarks. Then, the vertices are quantized into different quantization intervals according to the multiple QIM. Finally, multiple watermarks are embedded into different quantization intervals to reduce the interference among multiple watermarks, and the original watermarks are not needed in the process of watermark detection. We then conducted experiments to test the multiple watermark method’s robustness and capacity, with an emphasis on datasets with a lower data volume. The experimental results show that the proposed algorithm achieves good performance in terms of its robustness against common issues, such as vertices addition, data simplification, data cropping, and feature deletion; this holds true for both normal and small amounts of data. Additionally, it has a high multiple watermark capacity.

The ambiguity attack is to derive a valid watermark from a medium to defeat the ownership claim of the real owner. Most of the research suggests that it is difficult to design a provably secure non-ambiguity watermarking without a trusted third party. Recently, Li and Chang have provided a specific blind additive spread spectrum watermarking scheme as an example that is provably non-ambiguous. However, the proposed watermarking needs the length of watermark n > 3.07 × 10 9 according to our analysis. In this paper, a framework for quantization based watermarking schemes and non-blind spread spectrum watermarking scheme to achieve non-ambiguity is proposed. As a result, many of the existent watermarking schemes can achieve provable non-invertibility via using this framework, and an nonambiguity ownership verification protocol without a trusted third party may be constructed. We have obtained the close form solution of false positive rate for the underlying quantization based schemes and spread spectrum watermarking schemes (both blind and non-blind). The length of key of pseudo-random sequence generator (PRSG) is extended to m = c × n , the cardinality of the valid watermark set is extended to vWv = 2 m = 2 c,n , thus leading to more security to exhaustive searching attack than the Li and Chang's scheme, which has m = sn. In addition, the required length of watermark becomes much shorter than that required in the Li and Chang's scheme. At last, we propose a noninvertible and robust quantization-based watermarking scheme with the length of watermark being n=1024 .

A blind robust digital watermarking using invariant exponent moments