Digital Watermarking Technology Based on DCT and Neural Net

The traditional binary image is no longer sufficient to bring richer information in modern production and life. Color images have more information data than binary images. Based on the development of color image models and digital watermarking technology, this paper uses the Arnold scrambling and DWT-DCT method improves the robustness and invisibility of double color digital image watermarking. The encryption method improves the security of the watermark itself to a certain extent.

According to the picture archiving and communication system that have not introducing of the security mechanism yet, putting forward a security mechanism plan that based on digital watermarking and digital signature technology. Digital watermarking technology could authenticate the copyright of medical image effectively, and digital signature technology could authenticate the identity of sender and receiver. The PACS that introduced digital watermarking and digital signature technology could protect the interests for both hospitals and patients effectively in arbitration time, and became an important relying on for the development of remote medical.

Both watermark structure and embedding strategy affect robustness of image watermarks. Where should watermarks be embedded in the discrete cosine transform (DCT) domain in order for the invisible image watermarks to be robust? Though many papers in the literature agree that watermarks should be embedded in perceptually significant components, dc components are explicitly excluded from watermark embedding. In this letter, a new embedding strategy for watermarking is proposed based on a quantitative analysis on the magnitudes of DCT components of host images. We argue that more robustness can be achieved if watermarks are embedded in dc components since dc components have much larger perceptual capacity than any ac components. Based on this idea, an adaptive watermarking algorithm is presented. We incorporate the feature of texture masking and luminance masking of the human visual system into watermarking. Experimental results demonstrate that the invisible watermarks embedded with the proposed watermark algorithm are very robust.

Combined with the biometric identification technology and digital watermarking technology, a digital watermarking algorithm based on iris features is proposed. A secret key is used to generate the pseudorandom sequence which would have the cryptography in the sense of security. Through the two-scale wavelet transform and the combination of singular value decomposition, the robustness of the watermark can be improved. The experimental result shows that the watermarking algorithm is fit for iris feature and has strong robustness in noise resistance, geometric transform, compression and other aspects.

Since the Internet of Things(IoT) secret information is easy to leak in data transfer, a data secure transmission model based on compressed sensing(CS) and digital watermarking technology is proposed here. Firstly, for node coding end, the digital watermarking technology is used to embed secret information in the conventional data carrier. Secondly, these data are reused to build the target transfer data by the CS algorithm which are called observed signals. Thirdly, these signals are transmitted to the base station through the wireless channel. After obtaining these observed signals, the decoder reconstructs the data carrier containing privacy information. Finally, the privacy information is obtained by digital watermark extraction algorithm to achieve the secret transmission of signals. By adopting the watermarking and compression sensing to hide secret information in the end of node code, the algorithm complexity and energy consumption are reduced. Meanwhile, the security of secret information is increased. The simulation results show that the method is able to accurately reconstruct the original signal and the energy consumption of the sensor node is also reduced significantly in consideration of the packet loss.

As digital watermarking becomes an accepted and widely applied technology, a number of concerns regarding its reliability in typical application scenarios come up. One important and often discussed question is the robustness of digital watermarks against multiple embedding. This means that one cover is marked several times by various users with by same watermarking algorithm but with different keys and different watermark messages. In our paper we discuss the behavior of our PCM audio watermarking algorithm when applying multiple watermark embedding. This includes evaluation of robustness and transparency. Test results for multiple hours of audio content ranging from spoken words to music are provided.

A novel CNN based security guaranteed image watermarking generation scenario for smart city applications

The digital watermarking algorithm based on discrete Hopfield neural networks and singular value decomposition have been put forward in this paper. Currently, there are some shortcomings such as weak resistance on the attacks of geometric distortion and noise in some digital watermarking algorithm. Firstly, block-based singular value decomposition was applied for the original image to build the neural network model between the largest and other singular values which are coefficient. Secondly, the watermark information has been embedded in selecting larger contrasting image blocks. Finally, the neural networks were used for memorizing the original image and watermark information. While checking, the watermark was extracted by use of embedding watermarking image and associating original image and then the blind detection was realized. The results show that the watermark can be well extracted through the common image processing and compressing operations and the watermarking algorithm is with the good robustness in the geometric distortion.

Robustness is the key issue in the development of multi-bit watermarking algorithm. A new algorithm for robust multi-bit image watermarking based on Hidden Markov Model (HMM) in wavelet domain is proposed in this paper. The algorithm is characterized as follows: (1) the proposed blind detector based on vector HMM, which describes the statistics of wavelet coefficients, achieves significant improvement in performance compared to the conventional correlation detector; (2) adaptive watermark embedding scheme is applied to achieve the low distortion according to the Human Visual System (HVS); (3) optimal multi-bit watermark embedding strategy and maximum-likelihood detection for tree structure of vector HMM is proposed through system robustness analysis. Simulation results show that relatively high capacity for watermark embedding in low frequency subbands of wavelet domain is achieved with the proposed algorithm, and high robust results are observed against StirMark attacks, such as JPEG compression, additive noise, median cut and filter.

This paper presents a confidential text documents leakage investigation system, focused on leak channels by documents printing and screen photographing. Internal intruders may print confidential document, take paper copy out of protected perimeter, make document image by scanner and perform anonymous leak. Also, intruders may take a photo of printed confidential document or displayed on workstation screen using personal mobile phone. Described leakage channels are weakly covered by traditional DLP systems that are usually used by enterprises for confidential information leak protection. Digital watermark (DWM) embedding is chosen as a document protection mechanism by implying changing of document image visual representation. In case of confidential document anonymous leak embedded DWM would enable the employee to determine what leak intentionally or by security protocol violation. System architecture consists of different type components. Employees’ workstation components provide DWM embedding into documents, which are sent for printing or displayed on screen. Information about watermark embedding is sent to a remote server that aggregates marking facts and provides it to security officer during investigation. Text document marking algorithms are developed, which embed DWM into printed and displayed on screen documents. Screen watermark is embedded into interline space interval, information is encoded by sequence of lightened and darkened spaces. DWM embedding into printed documents is implemented by three algorithms: horizontal and vertical shift based, font fragments brightness changing based. Algorithms testing methodology is developed in view of the production environment, that helped to evaluate the application area of algorithms. Besides, intruder model was formulated, system security was evaluated and determined possible attack vectors.

Together with the rapid growth of Internet service, copyright violation problems, such as unauthorized duplication and alteration of digital materials, have increased considerably (Langelaar et al., 2001). Therefore copyright protection over the digital materials is a very important issue that requires an urgent solution. The watermarking is considered as a viable technique to solve this problem. Until now, numerous watermarking algorithms have been proposed. Most of them are image watermarking algorithms and relatively few of them are related with video sequences. Although image watermarking algorithms can be used to protect the video signal, generally they are not efficient for this purpose, because image watermarking algorithms does not consider neither temporal redundancy of the video signal nor temporal attacks, which are efficient attacks against video watermarking (Swanson et al., 1998). Generally, in the watermarking schemes for copyright protection, the embedded watermark signal must be imperceptible and robust against common attacks, such as lossy compression, cropping, noise contamination and filtering (Wolfgang et al., 1999). In addition, video watermarking algorithms must satisfy the following requirements: a blind detection, high speed process and conservation of video file size. The blind detection means that the watermark detection process does not require original video sequence, and the temporal complexity of watermark detection must not affect video decoding time. Also the file size of video sequence must be similar, before and after watermarking. Due to the redundancy of the video sequence, some attacks such as frame dropping and frame averaging can effectively destroy the embedded watermark, without cause any degradation to the video signal. A design of an efficient video watermarking algorithm must consider this type of attacks (Wolfgang et al., 1999). Basically, video watermarking algorithms can be classified into three categories: watermarking in base band (Wolfgang et al., 1999; Hartung & Girod 1998; Swanson et al., 1998; Kong et al., 2006), watermarking during video coding process (Liu et al., 2004; Zhao et al., 2003; Ueno 2004; Noorkami & Mersereau 2006) and watermarking in coded video sequence (Wang et al., 2004; Biswas et al., 2005; Langelaar & Lagendijk 2002). In the base band technique, the watermarking process is realized in uncompressed video stream, in which almost all image watermarking algorithms can be used, however generally computational complexity for watermark embedding and detection is considerably high for

With the rapid growth of the multimedia technology, copyright protection has become a very important issue, especially for images. The advantages of easy photo distribution are discarded by their possible theft and unauthorized usage on different websites. Therefore, there is a need in securing information with technical methods, for example digital watermarks. This paper reviews digital watermark embedding methods for image copyright protection, advantages and disadvantages of digital watermark usage are produced. Different watermarking algorithms are analyzed. Based on analysis results most effective algorithm is chosen – differential energy watermarking. It is noticed that the method excels at providing image integrity. Digital watermark embedding system should prevent illegal access to the digital watermark and its container. Requirements for digital watermark are produced. Possible image attacks are reviewed. Modern modifications of embedding algorithms are studied. Robustness of the differential energy watermark is investigated. Robustness is a special value, which formulae is given further in the article. DEW method modification is proposed, it’s advantages over original algorithm are described. Digital watermark serves as an additional layer of defense which is in most cases unknown to the violator. Scope of studied image attacks includes compression, filtration, scaling. In conclusion, it’s possible to use DEW watermarking in copyright protection, violator can easily be detected if images with embedded information are exchanged.

Commutative encryption and watermarking (CEW) is an emerging method that combines encryption technology with digital watermarking technology. It has the dual capability of secure transmission and copyright protection. However, the existing CEW methods for vector maps have good robustness in resisting geometric attacks but poor resistance to vertex attacks (e.g., addition, deletion, etc.). To solve this problem, here we propose a novel invariant-based CEW algorithm for vector maps, which consists of permutation-based encryption scheme and coordinates-based watermarking scheme. In the encryption scheme, the encryption key is generated via the Gaussian distribution method combined with the SHA-512 hash method; then, the double random position permutation strategy is applied to the vector map encryption. In watermarking embedding scheme, the original watermark image is scrambled via logistic chaotic encryption before embedding, and the coordinates of all the vertices are normalized. Then, the scrambled watermark image is embedded into the normalized coordinates. Results show that: proposed method is more robust to conventional attacks (e.g., vertex addition and deletion, reordering and data format conversion) and geometric attacks (e.g., scaling and translation). In addition, compared with the existing CEW methods for vector maps, the proposed method has higher security and stronger robustness against vertex attacks.

Digital watermarking technology has the advantages of easy implementation and capability of providing wide security services such as copyright protection, authentication and secret communication. In this paper, a novel image watermarking approach based on embedding watermarks in different domains, without any distortion of the watermarked image is used. In the spatial domain, the processing method is based on study of segmentation by fuzzy c-means clustering method (FCM) that outputs the zones of watermark embedding and respectively the associated appropriate embedding gain factors. However, in the DCT, we embedded the watermark into the coefficients in mid-band frequency of the selected blocks with different embedding strength. Experimental results show that the proposed scheme has good imperceptibility and high robustness to common image processing operators. Key words: Image watermarking, insertion force, Image segmentation, fuzzy C-mean (FCM), statistical features

Image watermarking preserves digital content. This study introduces a new watermarking approach employing Sub-Band Discrete Cosine Transform and Deep neural networks, GRNN and CNN. The method embeds robust, invisible watermarks in greyscale photos and compares the two neural network topologies. The watermark is added using sub-band DCT. Watermark embedding in low-frequency sub-bands resists photo processing. The binary watermark modifies sub-band DCT coefficients to determine embedding intensity, resisting signal deterioration, and assaults. GRNN and CNN neural networks extract watermarks accurately. CNN extracts hierarchical features from images, enabling robust watermark recovery even under distortions, whereas non-parametric GRNN stores the whole training data to create predictions. The watermarking approach is tested on several greyscale photos. PSNR, SSIM, MSE, and NCC measure performance. The watermark tests noise addition, compression, and filtering. Compare GRNN and CNN's watermark extraction strengths and shortcomings to assess image watermarking suitability.