Until today, digital image watermarking has not been large-scale used in the industry. The first reason is that the watermarking efficiency is low and the real-time performance cannot be satisfied. The second reason is that the watermarking scheme cannot cope with various attacks. To solve above problems, this paper presents a multi-domain based digital image watermarking scheme, where a fast DFT (Discrete Fourier Transform) based watermarking method is proposed for synchronization correction and an IWT-DCT (Integer Wavelet Transform-Discrete Cosine Transform) based watermarking method is proposed for information embedding. The proposed scheme has high efficiency during embedding and extraction. Compared with five existing schemes, the robustness of our scheme is very strong and our scheme can cope with many common attacks and compound attacks, and thus can be used in wide application scenarios.

A new method for hiding information in digital images is proposed. Our method differs from existing techniques in that the information is hidden in a mixture of colors carefully tuned on a specific device according to the device's signal-to-luminance (gamma) characteristics. Because these reproduction characteristics differ in general from device to device and even from model to model, the hidden information appears when the cover image is viewed on a different device, and hence the hiding property is device-dependent. To realize this, we modulated a cover image using two identically-looking checkerboard patterns and switched them locally depending on the hidden information. Reproducing these two patterns equally on a different device is difficult. A possible application of our method would be secure printing where an image is allowed to be viewed only on a screen but a warning message appears when it is printed.

In recent years, several reversible contrast-enhancement methods for color images using digital watermarking have been proposed. These methods can restore an original image from a contrast-enhanced image, in which the information required to recover the original image is embedded with other payloads. In these methods, the hue component after enhancement is similar to that of the original image. However, the saturation of the image after enhancement is significantly lower than that of the original image, and the obtained image exhibits a pale color tone. Herein, we propose a method for enhancing the contrast and saturation of color images and nearly preserving the hue component in a reversible manner. Our method integrates red, green, and blue histograms and preserves the median value of the integrated components. Consequently, the contrast and saturation improved, whereas the subjective image quality improved. In addition, we confirmed that the hue component of the enhanced image is similar to that of the original image. We also confirmed that the original image was perfectly restored from the enhanced image. Our method can contribute to the field of digital photography as a legal evidence. The required storage space for color images and issues pertaining to evidence management can be reduced considering our method enables the creation of color images before and after the enhancement of one image.

Software watermarking enables one to embed some information called “mark” into a program while preserving its functionality, and to read it from the program. As a definition of function preserving, Cohen et al. (STOC 2016) proposed statistical function preserving which requires that the input/output behavior of the marked circuit is identical almost everywhere to that of the original unmarked circuit. They showed how to construct watermarkable cryptographic primitives with statistical function preserving, including pseudorandom functions (PRFs) and public-key encryption from indistinguishability obfuscation. Recently, Goyal et al. (CRYPTO 2019) introduced more relaxed definition of function preserving for watermarkable signature. Watermarkable signature embeds a mark into a signing circuit of digital signature. The relaxed function preserving only requires that the marked signing circuit outputs valid signatures. They provide watermarkable signature with the relaxed function preserving only based on (standard) digital signature. In this work, we introduce an intermediate notion of function preserving for watermarkable signature, which is called computational function preserving. Then, we examine the relationship among our computational function preserving, relaxed function preserving by Goyal et al., and statistical function preserving by Cohen et al. Furthermore, we propose a generic construction of watermarkable signature scheme satisfying computational function preserving based on public key encryption and (standard) digital signature.

In this Letter, we propose a blind and robust multiple watermarking scheme using Contourlet transform and singular value decomposition (SVD). The host image is first decomposed by Contourlet transform. Singular values of Contourlet coefficient blocks are adopted to embed watermark information, and a fast calculation method is proposed to avoid the heavy computation of SVD. The watermark is embedded in both low and high frequency Contourlet coefficients to increase the robustness against various attacks. Moreover, the proposed scheme intrinsically exploits the characteristics of human visual system and thus can ensure the invisibility of the watermark. Simulation results show that the proposed scheme outperforms other related methods in terms of both robustness and execution time.

There are some technologies like QR codes to obtain digital information from printed matters. Digital watermarking is one of such techniques. Compared with other techniques, digital watermarking is suitable for adding information to images without spoiling their design. For such purposes, digital watermarking methods for printed matters using detection markers or image registration techniques for detecting watermarked areas are proposed. However, the detection markers themselves can damage the appearance such that the advantages of digital watermarking, which do not lose design, are not fully utilized. On the other hand, methods using image registration techniques are not able to work for non-registered images. In this paper, we propose a novel digital watermarking method using deep learning for the detection of watermarked areas instead of using detection markers or image registration. The proposed method introduces a semantic segmentation based on deep learning model for detecting watermarked areas from printed matters. We prepare two datasets for training the deep learning model. One is constituted of geometrically transformed non-watermarked and watermarked images. The number of images in this dataset is relatively large because the images can be generated based on image processing. This dataset is used for pre-training. The other is obtained from actually taken photographs including non-watermarked or watermarked printed matters. The number of this dataset is relatively small because taking the photographs requires a lot of effort and time. However, the existence of pre-training allows a fewer training images. This dataset is used for fine-tuning to improve robustness for print-cam attacks. In the experiments, we investigated the performance of our method by implementing it on smartphones. The experimental results show that our method can carry 96 bits of information with watermarked printed matters.

The security and reliability of Arabic text exchanged via the Internet have become a challenging area for the research community. Arabic text is very sensitive to modify by malicious attacks and easy to make changes on diacritics i.e. Fat-ha, Kasra and Damma, which are represent the syntax of Arabic language and can make the meaning is differing. In this paper, a Hybrid of Natural Language Processing and Zero-Watermarking Approach (HNLPZWA) has been proposed for the content authentication and tampering detection of Arabic text. The HNLPZWA approach embeds and detects the watermark logically without altering the original text document to embed a watermark key. Fifth level order of word mechanism based on hidden Markov model is integrated with digital zero-watermarking techniques to improve the tampering detection accuracy issues of the previous literature proposed by the researchers. Fifth-level order of Markov model is used as a natural language processing technique in order to analyze the Arabic text. Moreover, it extracts the features of interrelationship between contexts of the text and utilizes the extracted features as watermark information and validates it later with attacked Arabic text to detect any tampering occurred on it. HNLPZWA has been implemented using PHP with VS code IDE. Tampering detection accuracy of HNLPZWA is proved with experiments using four datasets of varying lengths under multiple random locations of insertion, reorder and deletion attacks of experimental datasets. The experimental results show that HNLPZWA is more sensitive for all kinds of tampering attacks with high level accuracy of tampering detection.

The two issues of art image creation and data hiding are integrated into one and solved by a single approach in this study. An automatic method for generating a new type of computer art, called stained glass image, which imitates the stained-glass window picture, is proposed. The method is based on the use of a tree structure for region growing to construct the art image. Also proposed is a data hiding method which utilizes a general feature of the tree structure, namely, number of tree nodes, to encode the data to be embedded. The method can be modified for uses in three information protection applications, namely, covert communication, watermarking, and image authentication. Besides the artistic stego-image content which may distract the hacker's attention to the hidden data, data security is also considered by randomizing both the input data and the seed locations for region growing, yielding a stego-image which is robust against the hacker's attacks. Good experimental results proving the feasibility of the proposed methods are also included.

We have developed a digital watermarking method that use neural networks to learn embedding and extraction processes that are robust against rotation and JPEG compression. The proposed neural networks consist of a stego-image generator, a watermark extractor, a stego-image discriminator, and an attack simulator. The attack simulator consists of a rotation layer and an additive noise layer, which simulate the rotation attack and the JPEG compression attack, respectively. The stego-image generator can learn embedding that is robust against these attacks, and also, the watermark extractor can extract watermarks without rotation synchronization. The quality of the stego-images can be improved by using the stego-image discriminator, which is a type of adversarial network. We evaluated the robustness of the watermarks and image quality and found that, using the proposed method, high-quality stego-images could be generated and the neural networks could be trained to embed and extract watermarks that are robust against rotation and JPEG compression attacks. We also showed that the robustness and image quality can be adjusted by changing the noise strength in the noise layer.

We propose a method of non-blind speech watermarking based on direct spread spectrum (DSS) using a linear prediction scheme to solve sound distortion due to spread spectrum. Results of evaluation simulations revealed that the proposed method had much lower sound-quality distortion than the DSS method while having almost the same bit error ratios (BERs) against various attacks as the DSS method.

We have proposed a novel concept of a digital watermarking technique for music data that focuses on the use of sound synthesis and sound effect techniques. This paper describes the details of our proposed technique that employs the distortion effect, one of the most common sound effects frequently utilized especially for guitar and bass instruments. This paper describes the experimental results of evaluating the resistance of the proposed technique against some basic malicious attacks utilizing MP3 coding, tempo alteration, pitch alteration, and high-pass filtering. It is demonstrated that the proposed technique potentially has appropriate resistance against such attacks except for the high-pass filtering attack. A technique for increasing the resistance against the high-pass filtering attack is also supplementarily discussed.

We introduce a notion of watermarking for cryptographic functions and propose a concrete scheme for watermarking cryptographic functions. Informally speaking, a digital watermarking scheme for cryptographic functions embeds information, called a mark, into functions such as one-way functions and decryption functions of public-key encryption. There are two basic requirements for watermarking schemes. A mark-embedded function must be functionally equivalent to the original function. It must be difficult for adversaries to remove the embedded mark without damaging the original functionality. In spite of its importance and usefulness, there have only been a few theoretical works on watermarking for functions (or programs). Furthermore, we do not have rigorous definitions of watermarking for cryptographic functions and concrete constructions. To solve the problem above, we introduce a notion of watermarking for cryptographic functions and define its security. Furthermore, we present a lossy trapdoor function (LTF) based on the decisional bilinear Diffie-Hellman problem problem and a watermarking scheme for the LTF. Our watermarking scheme is secure under the symmetric external Diffie-Hellman assumption in the standard model. We use techniques of dual system encryption and dual pairing vector spaces (DPVS) to construct our watermarking scheme. This is a new application of DPVS.

An autoencoder has the potential ability to compress and decompress information. In this work, we consider the process of generating a stego-image from an original image and watermarks as compression, and the process of recovering the original image and watermarks from the stego-image as decompression. We propose embedder and extractor neural networks based on the autoencoder. The embedder network learns mapping from the DCT coefficients of the original image and a watermark to those of the stego-image. The extractor network learns mapping from the DCT coefficients of the stego-image to the watermark. Once the proposed neural network has been trained, the network can embed and extract the watermark into unlearned test images. We investigated the relation between the number of neurons and network performance by computer simulations and found that the trained neural network could provide high-quality stego-images and watermarks with few errors. We also evaluated the robustness against JPEG compression and found that, when suitable parameters were used, the watermarks were extracted with an average BER lower than 0.01 and image quality over 35 dB when the quality factor Q was over 50. We also investigated how to represent the watermarks in the stego-image by our neural network. There are two possibilities: distributed representation and sparse representation. From the results of investigation into the output of the stego layer (3rd layer), we found that the distributed representation emerged at an early learning step and then sparse representation came out at a later step.

Generation of secure signatures suitable for spread-spectrum video watermarking is proposed. The method embeds a message, which is a two-dimensional binary pattern, into a three-dimensional volume, such as video, by addition of a signature. The message can be a mark or a logo indicating the copyright information. The signature is generated by shuffling or permuting random matrices along the third or time axis so that the message is extracted when they are accumulated after demodulation by the correct key. In this way, a message is hidden in the signature having equal probability of decoding any variation of the message, where the key is used to determine which one to extract. Security of the proposed method, stemming from the permutation, is evaluated as resistance to blind estimation of secret information. The matrix-based permutation allows the message to survive the spatial down-sampling without sacrificing the security. The downside of the proposed method is that it needs more data or frames to decode a reliable information compared to the conventional spread-spectrum modulation. However this is minimized by segmenting the matrices and applying permutation to sub-matrices independently. Message detectability is theoretically analyzed. Superiority of our method in terms of robustness to blind message estimation and down-sampling is verified experimentally.

We have proposed an audio watermarking method based on modification of sound pressure level between channels. This method is focused on the invariability of sound localization against sound processing like MP3 and the imperceptibility about slightly change of sound localization. In this paper, we investigate about tolerance evaluation against various attacks in reference to IHC criteria.

In this study, an anonymization infrastructure for the secondary use of data is proposed. The proposed infrastructure can publish data that includes privacy information while preserving the privacy by using anonymization techniques. The infrastructure considers a situation where ill-motivated users redistribute the data without authorization. Therefore, we propose a watermarking method for anonymized data to solve this problem. The proposed method is implemented, and the proposed method's tolerance against attacks is evaluated.

We evaluated a technique for protecting the copyright of digital data for 3-D printing. To embed copyright information, the inside of a 3-D printed object is constructed from fine domains that have different physical characteristics from those of the object's main body surrounding them, and to read out the embedded information, these fine domains inside the objects are detected using nondestructive inspections such as X-ray photography or thermography. In the evaluation, copyright information embedded inside the 3-D printed object was expressed using the depth of fine cavities inside the object, and X-ray photography were used for reading them out from the object. The test sample was a cuboid 46mm wide, 42mm long, and 20mm deep. The cavities were 2mm wide and 2mm long. The difference in the depths of the cavities appeared as a difference in the luminance in the X-ray photographs, and 21 levels of depth could be detected on the basis of the difference in luminance. These results indicate that under the conditions of the experiment, each cavity expressed 4 to 5bits of information with its depth. We demonstrated that the proposed technique had the possibility of embedding a sufficient volume of information for expressing copyright information by using the depths of cavities.

A lot of encryption and watermarking schemes have been developed as countermeasures to protect copyrights of broadcast or multicast content from malicious subscribers (traitors) that make pirate receivers (PRs) to use the content illegally. However, solo use of these schemes does not necessarily work well. Traitor tracing encryption schemes are a type of broadcasting encryption and have been developed for broadcasting and multicast services. There are multiple distinct decryption keys for each encryption key, and each service subscriber is given a unique decryption key. Any subscriber that redistributes his or her decryption key to a third party or who uses it and maybe other keys to make a PR can be identified with using the tracing algorithm of the scheme that is used by the services. However, almost all previous schemes have the same weakness; that is, they are vulnerable to an attack (content comparison attack). This is a concrete example such that solo use of the scheme does not work well. The attack involves multiple distinct decryption keys and a content-data comparison mechanism. We have developed a method, called complementary traitor tracing method (CTT), that makes traitor tracing schemes secure against content comparison attacks. It makes it impossible for PRs to distinguish ordinary content data from test data and makes traitor tracing schemes effective against all PRs, even those with multiple distinct decryption keys. CTT is made with a simple combination of schemes that are absolutely necessary. It makes broadcasting or multicast services secure.

In these days, we can see digital signages in many places, for example, inside stations or trains with the distribution of attractive promotional video clips. Users can easily get additional information related to such video clips via mobile devices such as smartphone by using some websites for retrieval. However, such retrieval is time-consuming and sometimes leads users to incorrect information. Therefore, it is desirable that the additional information can be directly obtained from the video clips. We implement a suitable digital watermarking method on smartphone to extract watermarks from video clips on signages in real-time. The experimental results show that the proposed method correctly extracts watermarks in a second on smartphone.

We propose a digital image watermarking method satisfying information hiding criteria (IHC) for robustness against JPEG compression, cropping, scaling, and rotation. When a stego-image is cropped, the marking positions of watermarks are unclear. To detect the position in a cropped stego-image, a marker or synchronization code is embedded with the watermarks in a lattice pattern. Attacks by JPEG compression, scaling, and rotation cause errors in extracted watermarks. Against such errors, the same watermarks are repeatedly embedded in several areas. The number of errors in the extracted watermarks can be reduced by using a weighted majority voting (WMV) algorithm. To correct residual errors in output of the WMV algorithm, we use a high-performance error-correcting code: a low-density parity-check (LDPC) code constructed by progressive edge-growth (PEG). In computer simulations using the IHC ver. 4 the proposed method could a bit error rate of 0, the average PSNR was 41.136 dB, and the computational time for synchronization recovery was less than 10 seconds. The proposed method can thus provide high image quality and fast synchronization recovery.