Robust Digital Watermarking Research Articles

Digital watermarking algorithm for QR code based on hybrid PSOGWO optimization

Abstract With the rapid development of digital media, QR codes have become widely used as an important medium for information transmission. However, this also presents serious security challenges, such as frequent image infringement and inevitable compression and scaling issues during data transfer. These challenges directly threaten the effectiveness and integrity of image information, and effective protection measures must be taken. Under this background, digital watermarking technology comes into being as an innovative method to enhance security. This paper presents an innovative Hybrid Particle Swarm Optimization and Gray Wolf optimization (HPG) algorithm, which combines the advantages of PSO and overcomes the limitations of traditional GWO algorithm. The algorithm is further improved by using Bernoulli chaotic mapping and nonlinear convergence factor. The experiments focus on the global and local search balance of the algorithm and its ability to resist repeated scaling attacks. The results show that the nonlinear convergence factor of HPG algorithm slows down the iteration speed at the initial stage, strengthens the global search, and avoids falling into the local optimal. In the later stage, the iteration is accelerated to improve the local search speed and convergence efficiency, thus optimizing the performance of the algorithm and ensuring the safety and quality of image information. In addition, the algorithm has better performance in balancing imperceptibility and robustness of digital watermarking, and its peak signal-to-noise ratio (PSNR) is higher. Even with many scaling iterations, the normalized correlation (NC) value is still close to 1. Compared with the existing typical algorithms, HPG algorithm is more robust to repeated scaling attacks.

Assessing the Effectiveness of Network Security Tools in Mitigating the Impact of Deepfakes AI on Public Trust in Media

The rising threat of deepfake technology challenges public trust in media, necessitating robust countermeasures. This study proposes the Anti-DFK framework, a comprehensive strategy to mitigate the spread of deepfakes on major social platforms such as Instagram, Facebook, YouTube, and Twitter. The framework integrates deep learning-based detection engines, digital watermarking, and advanced network access controls, including URL filtering, domain reputation filtering, content-type filtering, and Geo-IP blocking. Analyzing historical deepfake data, user engagement metrics, and public sentiment from Kaggle Datasets, the study employed deep learning models—CNNs, LSTMs, and Transformer-based—to evaluate detection capabilities, achieving the highest controlled environment accuracy of 0.97. Digital watermarking techniques were tested for robustness against various attacks, with the DCT method displaying significant resilience. Network access controls were assessed for their effectiveness in curtailing the spread of deepfakes, with content filtering proving the most effective by reducing dissemination by nearly 80%. Findings indicate a critical negative impact of deepfakes on public trust, underscoring the need for the integrated approach offered by the Anti-DFK framework. The study concludes that implementing these sophisticated detection tools, combined with robust digital watermarking and stringent network controls, can significantly enhance the integrity of media content and restore public confidence.

Robust digital image watermarking scheme with a fractional-order discrete-time chaotic scheme and DWT-SVD transform

A robust digital image watermarking system with a fractional-order discrete-time chaotic system and discrete wavelet transform-singular value decomposition is presented. The inclusion method inserts an encrypted image into the dynamics of an integer-order discrete-time chaotic system and the resulting cipher serves as a host image watermark. A watermarking function (DWT-SVD transform) watermarks a host image before the watermark is extracted and decrypted at the receiver. As a contribution, our suggested approach introduces a new watermarking system based on discrete-time chaotic systems, as well as a hybridization of integer and fractional-order systems to ensure the watermarking scheme’s robustness. Our method achieved good results in terms of robustness, with normalized cross correlation values above 0.99 when subjected to a range of attacks. Results of the simulation underline practicality and robustness achieved by this approach. They also indicate that the proposed system resists various attacks.

Survey of imperceptible and robust digital audio watermarking systems

Survey of imperceptible and robust digital audio watermarking systems

A robust digital image watermarking technique in LWT-DCT domain using particle swarm optimization and statistical distortion correction

A robust digital image watermarking technique in LWT-DCT domain using particle swarm optimization and statistical distortion correction

Robust digital image watermarking using cuckoo search optimization and probabilistic neural network

Robust digital image watermarking using cuckoo search optimization and probabilistic neural network

Research on Robust Digital Watermarking Based on Reversible Information Hiding

The development of modern Internet communication technology and the popularization of multimedia technology have brought convenience to the sharing and storage of multimedia information such as images, videos, and audio. However, at the same time, it has brought about the problem of copyright theft of multimedia information, causing serious information security risks. Digital watermarking technology embeds copyright information in multimedia information in an invisible way, which can effectively realize copyright protection and traceability of infringement. Aiming at the problem that the existing learning model-based methods cannot fully extract and fuse the features of carrier images and watermark images, a robust digital watermarking method based on reversible information hiding is proposed. First, a watermark embedding model based on reversible information hiding is established, and the features of the download volume image and the watermark image in different dimensions are fully extracted and fused to generate a dense image with excellent visual quality. Then, a watermark extraction model based on reversible information hiding is established, and a noise layer is added between the embedding and the extraction model, and the attacked dense image is input to the watermark extraction model to extract the watermark. Under the constraint of the loss function, the network model learns to embed watermark information in the area that is more robust to the attack and is not easy to cause visual quality degradation, so as to optimize the comprehensive performance of the method. Experimental results show that the proposed method effectively improves the imperceptibility and robustness.

Application of QR Code Watermarking and Encryption in the Protection of Data Privacy of Intelligent Mouth-Opening Trainer

QR(quick response) codes are widely used in offline to online channels to transfer information from promotional materials to mobile devices. Self-service medical equipment can record the data of each test, so the use of QR codes can realize the data exchange between patients and doctors, medical institutions, and self-service medical equipment, and create a medical information platform for health files. However, since anyone can easily read the information in the QR code, it is not conducive to the protection of patient privacy. Therefore, we propose a QR code encryption and decryption model based on robust digital watermarking. We implement digital watermarking through the Generative Adversarial Networks and increase the robustness of the watermark by adding noise to the model. At the same time, we encrypt and decrypt the QR code information through advanced encryption standards. Experimental results show that the proposed method can well protect the privacy of patients without affecting the data acquisition by patients and doctors.

Robust digital color image watermarking based on compressive sensing and DWT

Robust digital color image watermarking based on compressive sensing and DWT

Limit Bipolar Sequences for Patchwork-Based Robust Digital Audio Watermarking

Ensuring the robustness of digital audio watermarking under the influence of interference, various transformations and possible attacks is an urgent problem. One of the most used and fairly stable marking methods is the patchwork method. Its robustness is ensured by the use of expanding bipolar numerical sequences in the formation and embedding of a watermark in a digital audio and correlation detection in the detection and extraction of a watermark. An analysis of the patchwork method showed that the absolute values of the ratio of the maximum of the autocorrelation function (ACF) to its minimum for expanding bipolar sequences and extended marker sequences used in traditional digital watermarking approach 2 with high accuracy. This made it possible to formulate criteria for searching for special expanding bipolar sequences, which have improved correlation properties and greater robustness. The article developed a mathematical apparatus for searching and constructing limit-expanding bipolar sequences used in solving the problem of robust digital audio watermarking using the patchwork method. Limit bipolar sequences are defined as sequences whose autocorrelation functions have the maximum possible ratios of maximum to minimum in absolute value. Theorems and corollaries from them are formulated and proved: on the existence of an upper bound on the minimum values of autocorrelation functions of limit bipolar sequences and on the values of the first and second petals of the ACF. On this basis, a rigorous mathematical definition of limit bipolar sequences is given. A method for searching for the complete set of limit bipolar sequences based on rational search and a method for constructing limit bipolar sequences of arbitrary length using generating functions are developed. The results of the computer simulation of the assessment of the values of the absolute value of the ratio of the maximum to the minimum of the autocorrelation and cross-correlation functions of the studied bipolar sequences for blind reception are presented. It is shown that the proposed limit bipolar sequences are characterized by better correlation properties in comparison with the traditionally used bipolar sequences and are more robust.

Development of a cropping resilient watermarking scheme based on contourlet transform for secure IoT communication

The objective of this work is to propose a robust watermarking method as watermarking techniques are widely used today for preventing image altering and duplication. With the growth of image-based IoT applications nowadays, the need for developing robust digital watermarking techniques is of high demand. In this work, a robust yet highly perceptible watermarking scheme is proposed. The proposed scheme is based on the Contourlet Transform (CT) and Singular Value Decomposition (SVD) as the embedding domain in which the high-frequency components are chosen for embedding. The frequency domain is selected in order to make the watermarking scheme resists image attacks as the watermark is spreaded across different frequency bands in the cover image and hence the possibility of altering all the embedded bands is not possible as it will results in destroying the cover image. On the other hand, the Arnold transformation was used to insure secure IOT communication where the Arnold transform is applied to the binary logo watermark before embedding for a more secure design. In this context, the host image has been decomposed into the first level of contourlet transform and the highest frequency sub-bands are selected for embedding after performing the SVD on those bands where the SVD matrix is chosen to be the embedding domain. Moreover, This work aims to resist the cropping attack on images where PSNR values were above 52 dB and NC values ranged from 0.8 to 0.9 under various types of cropping attacks. In addition, the proposed method demonstrates its ability to resist various geometric and noise attacks such as JPEG compression, histogram equalization, gaussian noising and image brightening. Comparisons with state-of-the-art work demonstrate the proposed scheme's efficienc

A Hyper-Chaotically Encrypted Robust Digital Image Watermarking Method with Large Capacity Using Compress Sensing on a Hybrid Domain.

The digital watermarking technique is a quite promising technique for both image copyright protection and secure transmission. However, many existing techniques are not as one might have expected for robustness and capacity simultaneously. In this paper, we propose a robust semi-blind image watermarking scheme with a high capacity. Firstly, we perform a discrete wavelet transformation (DWT) transformation on the carrier image. Then, the watermark images are compressed via a compressive sampling technique for saving storage space. Thirdly, a Combination of One and Two-Dimensional Chaotic Map based on the Tent and Logistic map (TL-COTDCM) is used to scramble the compressed watermark image with high security and dramatically reduce the false positive problem (FPP). Finally, a singular value decomposition (SVD) component is used to embed into the decomposed carrier image to finish the embedding process. With this scheme, eight grayscale watermark images are perfectly embedded into a carrier image, the capacity of which is eight times over that of the existing watermark techniques on average. The scheme has been tested through several common attacks on high strength, and the experiment results show the superiority of our method via the two most used evaluation indicators, normalized correlation coefficient (NCC) values and the peak signal-to-noise ratio (PSNR). Our method outperforms the state-of-the-art in the aspects of robustness, security, and capacity of digital watermarking, which exhibits great potential in multimedia application in the immediate future.

A highly robust and secure digital image watermarking using modified optimal foraging algorithm - based SVM classifier and hyperchaotic Fibonacci Q-matrix

Transmission media is at rise over the internet, due to which the copyright risk is alarming. In such situation, enhanced security is the main concern. Digital image watermarking is the technique that ensures the copyright protection, security, and authenticity of the digital image. This research work recommends a highly secured and robust digital image watermarking system. In this method, the cover image is confused by arbitrarily generated numbers by a six-dimensional hyperchaotic technique, then this permuted image is scattered by applying the Fibonacci Q matrix to generate a scattered host image. This scattered image is decomposed up to 3 levels through DWT and the low pass sub-band caused by DWT are further decomposed by SVD. Singular values generated by SVD are used for watermark embedding as a slight change in the value does not affect the image quality. SVM classifier is used to classify the appropriate location to insert the scattered binary watermark. In this method SVM parameters are optimized by a modified optimal foraging algorithm, so that classification error can be reduced. Pixel rearrangement of the watermark image and host image makes the proposed method more secure, and it is highly robust as SVM is trained to classify locations that are less distorted by noise. Experimental outcomes depicts that the proposed method is accurate and better to the current cutting-edge methods in terms of security and robustness of digital image watermarking, as PSNR is approx. 72db and NC values are 1 after applying all the possible attacks.

A Wavelet Based Digital Image Watermarking Technique through Encryption with DCT

Recently, due to the increase in popularity of the Internet, the problem of digital data security over the Internet is increasing at a phenomenal rate. Watermarking is used for various notable applications to secure digital data from unauthorized individuals. Digital image watermarking is an attractive research area since it protects the multimedia data from unauthorized access. Digital images are widely communicated over the internet. The security of digital images is an essential and challenging task on shared communication channel. In the era of big data and networking, it is necessary to develop a secure and robust digital watermarking scheme with high computational efficiency to protect copyrights of digital works. Digital watermarking is need for the security of digital images to achieve security goals, i.e. confidentiality, integrity and availability. With the use of sophisticated signal/image processing algorithms, manipulations and duplications of audio, images, and videos are much easier. Hence, content authentication through encryption and resistance to general attacks such as noise, compression, and geometric has become an urgent and important issue. Hence in this work a wavelet based digital image watermarking technique through encryption with DCT (Discrete Cosine Transform) is presented that can guarantee robustness of image against salt and pepper attack.

A State of Art Comparison of Robust Digital Watermarking Approaches for Multimedia Content (Image and Video) Against Multimedia Device Attacks

A State of Art Comparison of Robust Digital Watermarking Approaches for Multimedia Content (Image and Video) Against Multimedia Device Attacks

Systematic Literature Review: Rancang Bangun Image Digital Watermarking

Digital Image Watermarking is a technology used in information security applications such as protection of digital image content and copyright protection. Digital image watermarking is an interesting area of research because it protects multimedia data from unauthorized access. To design an efficient and robust digital image watermarking system, a balance must be maintained. In this Systematic Literature Review (SLR), we conduct a brief review of the literature on digital image watermarking on journal papers published from 2018. Watermarking algorithms can be classified based on different criteria. Depending on the particular application, the watermarking algorithm must meet certain requirements. The expected result of this research is to know what digital image watermarking is, what it is for and is it useful to do digital image watermarking.

Robust and optimum color image watermarking method based on a combination of DWT and DCT

A hybrid and robust digital image watermarking is suggested by using advantages of both frequency domain and wavelet domain. In this method, the most suitable color component of the host image and the most efficient wavelet sub-band are chosen, concluding from the comprehensive experiments. In this paper, three parallel stages are used to embed and extract the watermark message. After transforming color component of the host image into the wavelet domain, some preprocessing with Discrete Cosines Transformers are applied, and then the watermark message is embedded into the best range by using a secret key. By detecting the rank of constructed detection matrices and voting among three output bits, the watermark bit is extracted. Simulation results demonstrate that the proposed method, besides the high robustness against Gaussian noise-based attacks especially AWGN, has performed well in imperceptibility and embedding capacity factors.

A robust digital video watermarking based on CT-SVD domain and chaotic DNA sequences for copyright protection

A robust digital video watermarking based on CT-SVD domain and chaotic DNA sequences for copyright protection

Robust speech watermarking by a jointly trained embedder and detector using a DNN

This paper utilizes deep neural networks for robust digital watermarking and authentication of speech signals. We present two adversarial neural networks, called embedder and detector. The embedder network tends to achieve imperceptible watermark embedding by minimizing the differences between the original and watermarked signals. The detector strives towards errorless watermark detection. We have proposed joint optimization of these two networks to achieve a trade-off between these requirements. Two models are trained, one with raw speech signals and another with STFT signal representations. Proposed techniques are tested on attacked audio recordings with measures such as SNR, PESQ, BER, and bps. The proposed system achieves high robustness to common watermarking attacks with BERs well below 1%. SNR values greater than 38 dB and PESQ values of 4.33 demonstrate that the difference in original and watermarked signals is negligible. In comparison with other approaches, our scheme shows good overall performance in terms of imperceptibility, robustness, and capacity.

A Multi-level Watermarking Algorithm for RasterGeographic Data Based on Watermark Information Segmentation Mechanism

This paper presents a multi-level digital watermarking algorithm suitable for raster geographic data. First, the new problems caused by the multi-level distribution of raster geographic data and its impact on watermark embedding/detection are analyzed; and then, a watermark information segmentation mechanism is designed, the multi-level watermark embedding strategy is established on this basis, thereby building the multi-level digital watermarking algorithm of raster geographic data based on the watermark segmentation mechanism with the traditional robust digital watermarking algorithm as the prototype; finally, the experimental comparison and analysis of the multi-level watermarking algorithm and the prototype algorithm are made. Results show that the proposed multi-level digital watermarking algorithm not only maintains the performance of the prototype algorithm, but also effectively solves new problems caused by the multi-level circulation of raster geographic data, such as multi-copyright protection and multi-user tracking, and has a high practical value.