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In past few years relational databases watermarking has emerged a great topic for research because of increase in use of relational databases. The basic need for relational database watermarking is to prevent data from illegal access by providing copyright protection, tamper detection and maintaining integrity. To serve this purpose many database watermarking techniques have been addressed with different algorithm and cover type. With the use of watermarking unauthorized duplication and distribution can be detected. The watermarking scheme should be able to meet some important challenges: 1). The scheme should be capable enough to bear attacks so that the watermark doesn’t get corrupted 2). The technique should be data preserving i.e. the error introduced into database as watermark information should not affect the value of data. The basic purpose of this paper is to review and analyse some existing image based database watermarking techniques.

Digital watermarking has been widely studied as a method of protecting the intellectual property rights of digital images, which are high value-added contents. Recently, studies implementing these techniques with neural networks have been conducted. This paper also proposes a neural network to perform a robust, invisible blind watermarking for digital images. It is a convolutional neural network (CNN)-based scheme that consists of pre-processing networks for both host image and watermark, a watermark embedding network, an attack simulation for training, and a watermark extraction network to extract watermark whenever necessary. It has three peculiarities for the application aspect: The first is the host image resolution’s adaptability. This is to apply the proposed method to any resolution of the host image and is performed by composing the network without using any resolution-dependent layer or component. The second peculiarity is the adaptability of the watermark information. This is to provide usability of any user-defined watermark data. It is conducted by using random binary data as the watermark and is changed each iteration during training. The last peculiarity is the controllability of the trade-off relationship between watermark invisibility and robustness against attacks, which provides applicability for different applications requiring different invisibility and robustness. For this, a strength scaling factor for watermark information is applied. Besides, it has the following structural or in-training peculiarities. First, the proposed network is as simple as the most profound path consists of only 13 CNN layers, which is through the pre-processing network, embedding network, and extraction network. The second is that it maintains the host’s resolution by increasing the resolution of a watermark in the watermark pre-processing network, which is to increases the invisibility of the watermark. Also, the average pooling is used in the watermark pre-processing network to properly combine the binary value of the watermark data with the host image, and it also increases the invisibility of the watermark. Finally, as the loss function, the extractor uses mean absolute error (MAE), while the embedding network uses mean square error (MSE). Because the extracted watermark information consists of binary values, the MAE between the extracted watermark and the original one is more suitable for balanced training between the embedder and the extractor. The proposed network’s performance is confirmed through training and evaluation that the proposed method has high invisibility for the watermark (WM) and high robustness against various pixel-value change attacks and geometric attacks. Each of the three peculiarities of this scheme is shown to work well with the experimental results. Besides, it is exhibited that the proposed scheme shows good performance compared to the previous methods.

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.

This paper discusses a new approach to ‘watermarking’ digital signals using linear frequency modulated or ‘chirp’ coding. The principles underlying this approach are based on the use of a matched filter to provide a reconstruction of a chirped code that is uniquely robust, i.e. in the case of very low signal-to-noise ratios. Chirp coding for authenticating data is generic in the sense that it can be used for a range of data types and applications (the authentication of speech and audio signals, for example). The theoretical and computational aspects of the matched filter and the properties of a chirp are revisited to provide the essential background to the method. Signal code generating schemes are then addressed and details of the coding and decoding techniques considered.

Several of the authors question the efficacy of copyright, which is increasingly regarded as benefiting multinational organisations rather than individual authors and performers. Others are less critical of copyright per se, but question its ability to meet the new challenges of a digital era. Some of the specific issues covered include: law and international transactions of copyrighted material; economic analysis of copyright and freedom of expression; music licensing in the digital age; the role of copyright in stimulating cultural development; internet distribution of copyright material; and the problems of licensing museum images.

As an important means of information security and copyright protection, digital watermarking technology has been extensive researched and widely applied; it proves data’s ownership or integrity by embedding secret information into raw data, thus achieves the purpose of copyright protection and information security. Based on the analysis and research of wavelet transformation, this study achieves to embed digital watermarking into the oracle bone inscriptions rubbings. Experimental results show that this method has a stronger robustness to altering and cutting of images.

In this chapter, we will introduce digital watermarking systems and quality evaluation algorithms for audio and speech signals. Originally designed for copyright protection, digital watermarking is a technique that embeds some data to the host signal to show the copyright information. The embedded data, or the watermark, cannot be eliminated from the host signal with normal use or even after some attacks. In the first part of this chapter, we introduce a generic framework of digital watermarking systems. Several properties and application of the watermarking systems are then described. Focused on audio and speech signals, we divide the watermarking algorithms into robust and fragile ones. Different concerns and techniques are described for each category. In the second part of this chapter, a novel watermarking algorithm for audio and speech quality evaluation is introduced together with some conventional quality evaluation standards.

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.

Digital Watermarking: Status, Limitations and Prospects

Invisible Digital watermarks have been proposed as a method for discouraging illicit copying and distribution of copyright material. In recent years it has been recognized that embedding information in a transform domain leads to more robust watermarks. In particular, several approaches based on the wavelet transform have ben proposed to address the problem of image water marking. The advantage of the wavelet transform relative to the DFT or DCT is that it allows for localized water marking of the image. A major difficulty, however, in watermarking in any transform domain lies in the fact that constraints on the allowable distortion at any pixel are specified in the spatial domain. In order to insert an invisible watermark, the current trend has been to model the Human Visual Systems and specify a masking function which yields the allowable distortion for any pixel. This complex function combines contrast, luminance, color, texture and edges. The watermark is then inserted in the transform domain and the inverse transform computed. The watermark is finally adjusted to satisfy the constraints on the pixel distortions. However this method is highly suboptimal since it leads to irreversible losses at the embedding stage because the watermark is being adjusted in the spatial domain with no care for the consequences in the transform domain.

The Digital Millennium Copyright Act tasked the Copyright Office with conducting a triennial rulemaking to grant exemptions to a ban on circumventing access controls on copyrighted works, and five rulemakings have been conducted since the 1998 passage of the Act. Drawing on a decade of experience with the rulemaking process, this Note explores lessons learned from the most recent round and suggests practices the Copyright Office could adopt to make the rulemaking more efficient and more closely aligned with Congress’s intent.

The security of multimedia's transmission on Internet is very important. In this paper we have discussed digital watermarking technology and the protocol of fair exchange. Then, the scheme of network manufacture products electronic trading based on fair exchange protocol and digital watermarking technology is presented in this paper. Experiments show that the scheme has the properties of fair exchanging and copyright protection, and it is a good scheme to solve security and fairness problems.

With the rapid development of Generative Artificial Intelligence (AIGC) technology, the creation and dissemination of digital content have entered a new era. However, issues such as copyright protection, security, and traceability of these generated contents are gradually becoming prominent, and effective technological measures are still needed to address them. Digital watermarking technology, as an effective means to solve these problems, has a wide range of application prospects. This study proposes a new digital watermarking algorithm specifically targeting the characteristics of AIGC generated content, aiming to address the shortcomings of existing technologies in terms of concealment, robustness, and security. By comparing and analyzing existing technologies, improvement plans were proposed and optimized and experimentally verified. The experimental results show that the proposed algorithm can effectively improve the copyright protection capability of content while ensuring the concealment of watermarks, and has good application prospects.

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 text is the most frequent interchange form of data that could hold sensitive information such as audit firms, banks, and educational institutes. This sensitive information needs to preserve its integrity and originality so that it could not only secure the data but also helps to identify ownership of text documents. This paper presents a novel and invisible digital watermarking approach for the secure exchange of text documents over the internet. Digital watermarking serves from the last decade for detection of forgery and tempering from digital text documents and maintained the copyright and authentication successfully. Many states of the art watermark techniques achieve high imperceptibility, robustness, and high hidden capacity; unfortunately failed to maintain the balance among these three conflicting parameters. As resolvent, we propose an intelligent Three-Level Digital Watermarking (3LDW) system for text documents copyright protection. 3LDW system can be applied to Microsoft Word objects, document open spaces, and text feature coding without affecting the content of the original document. Experimental results reveal that our proposed 3LDW system strongly resist against formatting attacks and efficiently preserves the imperceptibility. Additionally, embedding capacity analysis demonstrates a prominent improvement of the proposed system as compared to other similar approaches.