The advancements in communication and information technologies have substantially enabled the extensive distribution and modification of high-resolution color images. Although this accessibility provides many advantages, it also presents risks related to security. Specifically, when image modification is conducted with malicious intent, exceeding typical artistic or enhancement objectives, it can cause significant moral or economic harm to the image owner. To address this security requirement, this study presents an innovative semi-fragile watermarking algorithm designed specifically for high-resolution color images. The proposed method utilizes Discrete Cosine Transform domain watermarking implemented via Quantization Index Modulation with Dither Modulation. It incorporates several elements, such as convolutional encoding, a denoising convolutional neural network, and a very deep super-resolution neural network. This comprehensive strategy aims to provide ownership verification using a logo watermark, in conjunction with tamper detection and content self-recovery mechanisms. The self-recovery criterion is determined using a thumbnail image, created by downscaling to standard definition and applying JPEG2000 lossy compression. The resultant multifunctional design enhances the overall security of the information. Experimental validation confirms the enhanced imperceptibility, robustness, and capacity of the proposed method. Its efficacy was additionally corroborated through comparative analyses using contemporary state-of-the-art algorithms.

Digital asset management systems (DAMS) handle different media data in a compressed and encrypted form. It is essential to watermark these compressed encrypted media items in the compressed-encrypted domain itself for tamper detection or ownership declaration or copyright management purposes. Attempting steganography technique is such a randomized bit stream can cause a poor degradation of the media quality. Thus it is important to choose an encryption scheme that is both secure and will allow watermarking in a predictable manner in the compressed encrypted domain. we propose a rainbow algorithm to watermark images and documents. We suggest using a stream cipher as the encryption algorithm. Although the suggested method embeds the watermark in the compressed-encrypted domain, the decrypted domain can be used to extract the watermark. Using the following watermarking schemes, we thoroughly examine the suggested algorithm's embedding capability, robustness, perceptual quality, and security: Spread Spectrum (SS), Scalar Costa Scheme Quantization Index Modulation (SCS-QIM), and Rational Dither Modulation (RDM). KEYWORDS: Encryption, Steganography techniques, Rainbow Algorithm.

Adaptive Video Dual Domain Watermarking Scheme Based on PHT Moment and Optimized Spread Transform Dither Modulation

With the prosperity of online social networks (OSNs), people usually share photos taken with their mobile phones to OSN, which is suitable for covert communication. However, these images have high quality factors (QFs) and will be JPEG recompressed with low QFs by OSNs, which precludes existing robust steganography methods using low QF images. Therefore, we propose a Postprocessing and precise dither Modulation based robust Adaptive Steganography method (PMAS) for high quality images. Precise dither modulation ensures the robustness of the modified coefficients and improves security by reducing the magnitude of modifications. Postprocessing amends the coefficients that changed after recompression to ensure the robustness of unmodified coefficients. Additionally, we devise heuristics to mitigate post-processing and explore the relationship between the modification magnitude and distortion assignment with novel scaling functions, which all contribute to security. The experimental results demonstrate that PMAS is competent for high quality images, and the effect of every module in PMAS is verified.

Visible Light Communication (VLC) is an emerging short-range optical communication technology that can alleviate spectrum congestion. However, VLC faces security problems with man-in-the-middle hijacking and bypass listening. Since the covert transmission of visible light information has the characteristics of strong concealment and difficult detection, VLC based on information hiding becomes a new paradigm to solve these security problems. This paper presents a method in which Red, Green, Blue (RGB) Light-emitting Diode (LED) is used to secure the VLC by using the information hiding technique. Specifically, a gammatone filter bank-based feature extraction method is suggested. This method extracts robust vector for information hiding and extraction. To hide and extract the information, a dither modulation information hiding scheme based on the adaptive optimization is proposed. The presented method uses dither modulation to hide information in the extracted feature vector, which can effectively improve the success rate of information extraction. On the basis of performance analysis, the superiority of the presented method is illustrated by comparing with the existing methods.

Through comparison with most frequency-domain digital watermarking approaches, the spread transform dither modulation (STDM) method exhibits a good embedding effect and is capable of meeting the requirements of blind extraction. However, the rotating attack is difficult to counter, and the cropping attack is seriously impacted by location factors. In addition, there exist numerous algorithms concentrate solely on the watermarking process, ignoring the image's security. In these views, our work proposes a two-dimensional hyperchaotic system, the so-named Chebyshev ICMIC cascade map with the Knuth–Durstenfeld method, aiming to enhance the security of digital watermarking systems. The scrambled pixels improve the anticropping attack effect through breaking the location correlation of watermark information. For the purpose of magnifying resistance to rotation attack impact, the radial harmonic Fourier moments subtraction coefficient matrix distribution expectation is appropriately adapted to carry out the rotation correction. The performed experiments reveal that the suggested improved STDM watermarking algorithm demonstrates better robustness and invisibility, resisting more attacks than the existing methodologies. Finally, the feasibility of the proposed methods is proved based on the simulation results.

How to improve the robustness to resist attacks and how to adaptively match the key parameters of the watermarking algorithm with the performance requirements to achieve the best performance in different applications are two hot issues in the research of audio watermarking algorithms. An adaptive and blind audio watermarking algorithm based on dither modulation and butterfly optimization algorithm (BOA) is proposed. Based on the convolution operation, a stable feature is designed to carry the watermark, which will improve the robustness by means of the stability of this feature to prevent the watermark loss. Blind extraction will be achieved only by comparing the feature value and the quantized value without the original audio. The BOA is used to optimize the key parameters of the algorithm which can be matched with the performance requirements by coding the population and constructing the fitness function. Experimental results confirm that this proposed algorithm can adaptively search for the optimal key parameters that match the performance requirements. Compared with other related algorithms in recent years, it exhibits strong robustness against various signal processing attacks and synchronization attacks.

In image watermarking, the locations where the watermark is embedded in the frequency domain and the embedding strength influence the overall performance of the blind watermarking procedure. The present paper aims to propose a new blind watermarking method based on the dither modulation by developing an automatic selection of the optimum embedding parameters that guarantee high-quality watermarked images and low bit error rates during the extraction process. The proposed automatic search method for the best discrete moments subsets is based on an evolutionary algorithm and adopts a specific coding strategy with a group of genes representing the embedding positions. The second part of the chromosome is reserved for the embedding strength coding, followed by the application of different evolutionary operators on the evolution pool. Our study explores the impact of maximum generation, population size, and cutting-point positions with different crossover and mutation rates. The performances under different attack conditions are evaluated, and a comparative study is established with other conventional selection methods and other discrete transforms. Results show that our proposed optimization algorithm baptized EWIMps achieves the best trade-off between robustness and imperceptibility with a peak signal-to-noise ratio varying from 28.33 dB to 59.87 dB and a normalized cross-correlation value from 0.707 to 1.

Adversarial robust image steganography against lossy JPEG compression

Analysis on unit maximum capacity of orthogonal multiple watermarking for multimedia signals in B5G wireless communications

In this letter, a wavelength-tunable Optical Time-Domain Reflectometer (OTDR) for Dense Wavelength Division Multiplexing Passive Optical Network (DWDM-PON) is proposed and experimentally demonstrated. An Integrated Tunable Laser Assembly (ITLA) serves as the light source permitting measurements of 80 DWDM channels in the C-band. Dither modulation is added to ITLA to depress coherent noise resulted from the narrow linewidth of the light source. Semiconductor Optical Amplifier (SOA) modulates the continuous light into pulsed light and meanwhile amplifies peak optical power of the pulsed light to 13 dBm. In addition, we optimize the wavelet denoising algorithm for further signal-noise ratio (SNR) enhancement. Dynamic range and spatial resolution of the proposed OTDR reach up to 16.2 dB and 2 m respectively. A DWDM-PON fiber link including an Arrayed Waveguide Grating (AWG) is measured to verify the system performances, and the OTDR profiles of different channels coincide with each other. The designed wavelength-tunable OTDR is shown to be appropriate for DWDM-PON.

Imperceptible–visible watermarking for copyright protection of digital videos based on temporal codes

Spread-Transform Dither Modulation Watermarking of Deep Neural Network

SHDM stands for Sphere-Hardening Dither Modulation and is a watermarking algorithm based on quantizing the norm of a vector extracted from the cover work. We show how SHDM can be integrated into a fully commutative watermarking-encryption scheme and investigate implementations in the spatial, DCT, and DWT domain with respect to their fidelity, robustness, capacity, and security of encryption. The watermarking scheme, when applied in the DCT or DWT domain, proves to be very robust against JPEG/JPEG2000 compression. On the other hand, the spatial domain-based approach offers a large capacity. The increased robustness of the watermarking schemes, however, comes at the cost of rather weak encryption primitives, making the proposed CWE scheme suited for low to medium security applications with high robustness requirements.

Traditional adaptive steganography is a technique used for covert communication with high security, but it is invalid in the case of stego images are sent to legal receivers over networks which is lossy, such as JPEG compression of channels. To deal with such problem, robust adaptive steganography is proposed to enable the receiver to extract secret messages from the damaged stego images. Previous works utilize reverse engineering and compression-resistant domain constructing to implement robust adaptive steganography. In this paper, we adopt modification with re-compression scheme to improve the robustness of stego sequences in stego images. To balance security and robustness, we move the embedding domain to the low frequency region of DCT (Discrete Cosine Transform) coefficients to improve the security of robust adaptive steganography. In addition, we add additional check codes to further reduce the average extraction error rate based on the framework of E-DMAS (Enhancing Dither Modulation based robust Adaptive Steganography). Compared with GMAS (Generalized dither Modulation based robust Adaptive Steganography) and E-DMAS, experiment results show that our scheme can achieve strong robustness and improve the security of robust adaptive steganography greatly when the channel quality factor is known.

Spread Transform Dither Modulation (STDM) has good performance in robustness against Additive White Gaussian Noise (AWGN) and re-quantization, so it has been widely used in image watermarking algorithms. However, STDM cannot resist Fixed Gain Attack (FGA). In the paper, we introduce an adaptive function into the traditional STDM algorithm, so that it can automatically adjust the amount of distortion according to the text line spacing in the document. Then we give an improved adaptive function to make our algorithm robust to FGA. Analysis and experimental results show that the algorithm proposed in this paper has good invisibility and high robustness against AWGN and FGA.

Using Deep learning for image watermarking attack

Just noticeable distortion (JND) and visual attention (VA), which are two widely used mathematical models of human visual system (HVS) that aim to simulate the human brain mechanism, are sufficiently explored and applied to many researches including digital watermarking. The activity of human brain, however, is extremely complex and it can be more limited due to complicated fusion of spatial saliency for image domain. In this paper, we propose a novel VA guided JND model in which we fuse the final attention map from the low-level features by using two laws of Gestalt principle. Firstly, we demonstrate a classic JND model in DCT domain, which consists of spatial contrast sensitivity function (CSF), luminance adaptation (LA) and contrast masking (CM). The foveation effect and orientation feature are considered to obtain the CSF and CM factor. The foveation effect is affected by spatial attention, and the orientation features are modeled for CM effect together with traditional block texture strength through three direction-based AC coefficients in DCT domain. The attention features are integrated with a novel Gestalt principle-based weighting mechanism for the final block-based VA model, which is then used to modulate JND profiles with two non-linear functions. Finally, the proposed VA-guided JND model is incorporated into a logarithmic spread transform dither modulation (L-STDM) watermarking scheme. Experimental results show that the newly proposed algorithm can achieve good performance in term of robustness and get better visual quality.

This paper proposes an audio multi-watermarking scheme based on Gram–Schmidt orthogonalization. A random signal generator is applied to the host audio signal to generate the target segment for the local watermarking, thus improving the imperceptibility compared with the conventional global watermarking. The discrete cosine transform low-frequency coefficients of high stability are selected as watermark embedder, to ensure the robustness of this scheme. Consequently, the Gram–Schmidt orthogonalization process is employed to generate a set of orthogonal vectors, into which the spread transform dither modulation is applied to, respectively, embed the multiple watermark messages simultaneously. The orthogonality ensures that multiple watermark messages can be independently extracted without compromising the robustness against attacks. By embedding the multiple watermark messages into the same segment of the host audio signal, the watermark embedding capacity can be greatly enhanced while preserving the imperceptibility and robustness. A variety of experiments are conducted, and the results indicate the good performance of the proposed scheme. The proposed scheme has demonstrated superior performance gains over the state-of-the-art methods.

This paper presents a lifting wavelet transform (LWT)-based blind audio watermarking scheme designed for tampering detection and self-recovery. Following 3-level LWT decomposition of a host audio, the coefficients in selected subbands are first partitioned into frames for watermarking. To suit different purposes of the watermarking applications, binary information is packed into two groups: frame-related data are embedded in the approximation subband using rational dither modulation; the source-channel coded bit sequence of the host audio is hidden inside the 2nd and 3rd -detail subbands using 2N-ary adaptive quantization index modulation. The frame-related data consists of a synchronization code used for frame alignment and a composite message gathered from four adjacent frames for content authentication. To endow the proposed watermarking scheme with a self-recovering capability, we resort to hashing comparison to identify tampered frames and adopt a Reed–Solomon code to correct symbol errors. The experiment results indicate that the proposed watermarking scheme can accurately locate and recover the tampered regions of the audio signal. The incorporation of the frame synchronization mechanism enables the proposed scheme to resist against cropping and replacement attacks, all of which were unsolvable by previous watermarking schemes. Furthermore, as revealed by the perceptual evaluation of audio quality measures, the quality degradation caused by watermark embedding is merely minor. With all the aforementioned merits, the proposed scheme can find various applications for ownership protection and content authentication.