With the widespread adoption of smart devices and social networking platforms, the development of robust image steganography techniques for public lossy channels has become increasingly crucial. Among JPEG-resistant steganographic methods, PMAS (Postprocessing and precise dither Modulation based robust Adaptive Steganography) has demonstrated superior performance by utilizing high-quality images and maintaining resilience against aggressive compression. This method achieves remarkable concealment in user-shared images, presenting substantial challenges to public communication security. To counter this threat, we propose a specialized lightweight Scale-Free Network for mining Clues in downward JPEG-resistant steganography (SF-ClueNet), specifically designed to identify vulnerabilities in PMAS despite its sophisticated anti-detection mechanisms. Departing from conventional approaches that depend on high-pass filter residuals, SF-ClueNet extracts comprehensive global statistical features, enabling effective detection of dispersed steganographic artifacts. When integrated with lightweight residual feature miner, our method maintains pattern recognition capabilities as image dimensions increase, ensuring consistent detection performance. Experimental results demonstrate that SF-ClueNet significantly enhances detection accuracy, exhibits robust performance against data distribution shifts with minimal transfer loss, and supports direct analysis of high-resolution images. These advanced capabilities position SF-ClueNet as a viable and efficient solution for practical steganalysis applications across diverse operational environments.

The proliferation of video applications has exacerbated digital piracy issues, notably evidenced by unauthorized video digital editing and camcording processes. While existing research has introduced robust watermarking methods to safeguard video copyrights, these methods often address specific attack scenarios, limiting their overall efficacy. To address this problem, we propose a robust blind video watermarking scheme based on Frequency-Spherical Cavity Transformation (FSCT), offering a comprehensive solution for both digital editing and camcording processes. Our approach treats the spatial and temporal aspects of the video as a 3D cube, utilizing FSCT to ensure temporal translational invariance and resilience against spatial attacks. To mitigate artifacts induced by motion characteristics, we analyze the properties of FSCT and introduce a visual quality optimization strategy, enhancing imperceptibility while ensuring robustness. Simultaneously, during extraction process, the watermark can be successfully retrieved from video camcording with only a specified time interval, eliminating the need for temporal synchronization. Through extensive experimentation, the proposed method exhibits superior robustness against digital editing and camcording compared to existing methods.

In watermarking schemes, deriving the geometric invariants of the multimedia content is crucial for modern watermarking against geometric deformations. The invariants based on orthogonal moments can effectively describe the semantic content of multimedia due to their excellent mathematical properties. Modulating watermarked signals into these invariants can yield satisfactory geometric robustness. However, with the emerging risks posed by generative large models, the current theoretical analysis of the relationship between invariants and watermarking is still limited, and the intrinsic connection between them is neglected to varying degrees when designing moments-based watermarking schemes. To bridge this gap, we propose a set of design principles, including the texture complexity priority principle, uniform zeros distribution priority principle, and invariants conjugation priority principle, and reveal the critical influence of the mathematical properties of moments on video watermarking. Based on the above principles, we also propose a texture-aware adaptive video watermarking scheme based on orthogonal moments. Extensive experiments show that the proposed video watermarking scheme outperforms state-of-the-art watermarking algorithms regarding imperceptibility, robustness, and computational complexity.

The prevalence of digital content leakage via screen capture highlights the urgent need for robust watermarking solutions capable of withstanding cross-media transmission. Current approaches primarily focus on developing watermarking techniques resilient to screen-shooting distortions, where distinguishing the watermark signal from these distortions is paramount. In contrast, our study addresses an inverse problem by investigating the generation patterns of noise during screen-shooting and considering them as feasible representations of watermark signals. Leveraging Moiré patterns as one of the distortion signals naturally generated by the interaction between electronic screens and camera sensors, we propose Moiré-watermark, presenting watermark information encoded into meticulously crafted Moiré patterns within images. To enhance the naturalness of Moiré-watermark amidst the irregularities of screen-shooting Moiré patterns, we encode watermark signals using gratings at different angles. A corresponding angle-based decoding method facilitates effective blind extraction of watermarks. Comprehensive experimental evaluations under diverse conditions of distance, angle, lighting, and across various capturing and display devices, alongside comparisons with existing methods, validate the superior performance of Moiré-watermark.

With the rapid development of mobile Internet and video applications, robust video watermarking technology has become a focal area of research for protecting and tracking intellectual property rights in digital media. An important characteristic of video is that it has both spatial and temporal properties. Previous studies in video watermarking have primarily focused on either spatial or temporal distortions and did not uniformly consider all types of video distortion, which restricts the robustness of video watermarking. In this paper, a novel robust blind video watermarking is proposed by exploring consistent spatio-temporal distortion and stable 3-D DCT coefficients. Our method achieves stronger robustness by uniformly treating the spatial and temporal distortions of the video. The properties of the stable 3-D DCT coefficients are mathematically proved, which makes the scheme generalizable. Extensive experiments have demonstrated that our method is resistant to video compression (H.264/AVC, H.265/HEVC) attacks, geometric attacks, and temporal domain attacks, and outperforms the current state-of-the-art video watermarking schemes.

Existing video watermarking embeds robust watermarks in each frame of the video for copyright protection and tracking. However, just as any content written on a blank paper is easily perceived, embedding watermarks in the texture-poor frames impairs imperceptibility. Common geometric attacks such as scaling and rotation pose a significant challenge to the existing video watermarking. Image watermarking based on moments is robust against geometric attacks. However, moment-based watermarking is difficult to migrate to the video due to its lack of perceptual guarantee and high computational cost. In this paper, we propose an adaptive video watermarking scheme by exploring the relationship between moments and video textures, which can adaptively select texture-rich frames to embed watermarks for perceptual guarantee. Furthermore, we utilize the properties of moment calculation in videos to optimize efficiency. Extensive experiments show that the proposed method can achieve better imperceptibility than existing methods while maintaining strong robustness.

Malicious video tampering and unauthorized distribution on social networks pose significant challenges in distinguishing authentic from altered content and raise copyright infringement concerns. Although numerous watermarking schemes have been developed to protect copyright, tamper detection and localization have not been adequately addressed. To this end, we propose RDFMark, a dual-functional solution offering a unified framework for copyright protection and tamper detection. RDFMark introduces a new paradigm in video tamper detection by embedding a robust watermark that survives diverse attacks, enabling the extraction of copyright information and tampering cues. Extensive experiments validate the effectiveness of RDF-Mark against common video tampering scenarios encountered during social network transmissions, such as masking, barrage insertion, and cropping. Furthermore, it demonstrates resilience to geometric distortions, strong compression, re-compression, and composite attacks on social networks.

Abstract Blind image watermarking is regarded as a vital technology to provide copyright of digital images. Due to the rapid growth of deep neural networks, deep learning-based watermarking methods have been widely studied. However, most existing methods which adopt simple embedding and extraction structures cannot fully utilize the image features. In this paper, we propose a novel Single-Encoder-Dual-Decoder (SEDD) watermarking architecture to achieve high imperceptibility and strong robustness. Precisely, the single encoder utilizes normalizing flow to realize watermark embedding, which can effectively fuse the watermark and cover image. For watermark extraction, we introduce a parallel dual-decoder to improve the imperceptibility and extracting ability. Extensive experiments demonstrate that better watermark robustness and imperceptibility are obtained by SEDD architecture. Our method achieves a bit error rate less than 0.1% under most attacks such as JPEG compression, Gaussian blur and crop. Besides, the proposed method also obtains strong robustness under combined attacks and social platform processing.

With the proliferation of smartphones, preserving the confidentiality of digital documents has become increasingly challenging. Document formats, such as PowerPoint (PPT), are particularly susceptible to unauthorized capture and leakage through smartphone cameras. In this letter, we propose a camera shooting resilient watermarking for PowerPoint presentation based on the PPT master layout backdrop, which exhibits two key properties. 1) Imperceptibility. We employ a difference-based embedding method on the PPT master layout backdrop to ensure good visual quality of the watermarked PPT. 2) Robustness. We design a distance-based selection method for embedding coefficients, ensuring the watermark's robustness under various shooting conditions. The experimental results demonstrate the robustness of our scheme against screen and projection shooting of PPT presentation, across diverse shooting distances, angles, and coverage levels of the PPT master layout backdrop.

In moment-based watermarking schemes, the accuracy of the moments is crucial for constructing robust watermarking schemes. The robustness of the watermarking scheme relies heavily on the proper representation of the moments. Despite the importance, current theoretical research on accuracy is very limited in watermarking techniques. To this end, we propose a novel robust image watermarking scheme based on accurate polar harmonic Fourier moments (PHFMs). Specifically, the accurate PHFMs computation based on polar pixel tiling with nearest neighbor interpolation (PPTN) is designed. This computation is general and used for embedder and extractor. This ingenious design eliminates geometric and numerical integration errors and also avoids the distortion interaction caused by watermarks. Also, an improved quantization strategy is applied to the embedding process, and satisfactory imperceptibility is obtained. The watermark is extracted without the host image. The experimental results show the excellent robustness of the proposed watermarking scheme to common image processing attacks, geometric attacks, and some kinds of compound attacks. The proposed scheme is superior to the state-of-the-art image watermarking schemes.

According to the Buckets effect, the capacity of a bucket depends on the length of the shortest board. This principle also applies to social networking platform resilient (SNPR) image watermarking, which should be comprehensive and free from significant shortcomings. In the frequency domain, the watermarked region is formed using log-polar coordinate mapping (LPM) and has a ring-like structure. However, this structure cannot be stretched or compressed, and it causes a streaking effect at the edges of the watermarked image. These issues have been addressed in the proposed method. Specifically, an adaptive optimization framework is used to adjust the embedding strength and range of the watermark, and multiple synchronization strategies are adopted to correct flip and aspect ratio. Compared with state-of-the-art works, the proposed method significantly improves the imperceptibility of the watermarked image and its robustness to various distortions and lossy transmission on social networking platforms (SNPs).

Digital images are widely used nowadays, carrying a great deal of information. However, copyright infringement of digital images occurs from time to time which poses a threat to the rights and interests of copyright owners and the security of information content. To deal with such problems, in this paper, we propose an adaptive robust watermarking scheme to protect the copyright of color digital images. Spread spectrum watermark and two kinds of synchronization information are embedded in the luminance and chrominance channels of the color image, respectively. The synchronization information helps to restore geometric distortions. We also design a pre-quantization strategy to mitigate the distortions caused by social platforms. To achieve better imperceptibility, we propose an adaptive strategy based on the peculiarities of Human Visual System to adjust the strength of watermark residuals. Experimental results demonstrate that the proposed method is equipped with comprehensive and balanced robustness against common image processing, geometric distortions, unknown processing from social platforms and keeps the watermarked images with excellent imperceptibility simultaneously.

In recent years, online video sharing platforms have been widely available on social networks. To protect copyright and track the origins of these shared videos, some video watermarking methods have been proposed. However, their robustness performance is significantly degraded under geometric deformations, which destroy the synchronization between the watermark embedding and extraction. To this end, we propose a novel robust blind video watermarking scheme by embedding the watermark into low-order recursive Zernike moments. To reduce the time complexity, we give an efficient computation method by exploring the characteristics of video and moments. The moment accuracy is greatly improved due to the introduction of a recursive computation method. Furthermore, we design an optimization strategy to enhance visual quality and reduce distortion drift of watermarked videos by analyzing the radial basis function. The robustness of the proposed scheme is verified by different attacks, including geometric deformations, length-width ratio changes, temporal synchronization attacks, and combined attacks. In practical applications, the proposed scheme effectively resists processing from video sharing platforms and screenshots taken with smartphones and PC monitors. The watermark is extracted without the host video. Experimental results show that our proposed scheme outperforms other state-of-the-art schemes in terms of imperceptibility and robustness.

Designing an efficient synchronization method for video watermarking under complex hybrid attacks is an urgent task due to the development of social networks and multimedia software. However, few existing watermarking methods can resist various complex attacks on the social network, such as scaling, frame rate conversion, and other strong hybrid attacks. To address this issue, we first analyze the relationship between the spatial and discrete cosine transform (DCT) domain and propose a robust video watermarking based on residual synchronization (RS) mechanism. In the RS mechanism, the spread-spectrum encoded RS unit and sync frames are generated according to the change rules obtained from the analysis to achieve robustness. On the other hand, the high-frequency energy average distribution (HFEAD) mechanism is designed by analyzing the effects of distortion drifts and texture features for watermark embedding to achieve good visual quality. Extensive experimental results show that the RS mechanism can effectively synchronize watermarks under various attacks, e.g., asymmetric cropping, resizing, scaling, etc., hybridized with strong recompression attacks. Moreover, the proposed scheme is resistant to screenshots and social platform transcoding.