A Novel High-Capacity Information Hiding Scheme Based on Improved U-Net

With the gradual introduction of deep learning into the field of information hiding, the capacity of information hiding has been greatly improved. Therefore, a solution with a higher capacity and a good visual effect had become the current research goal. A novel high-capacity information hiding scheme based on improved U-Net was proposed in this paper, which combined improved U-Net network and multiscale image analysis to carry out high-capacity information hiding. The proposed improved U-Net structure had a smaller network scale and could be used in both information hiding and information extraction. In the information hiding network, the secret image was decomposed into wavelet components through wavelet transform, and the wavelet components were hidden into image. In the extraction network, the features of the hidden image were extracted into four components, and the extracted secret image was obtained. Both the hiding network and the extraction network of this scheme used the improved U-Net structure, which preserved the details of the carrier image and the secret image to the greatest extent. The simulation experiment had shown that the capacity of this scheme was greatly improved than that of the traditional scheme, and the visual effect was good. And compared with the existing similar solution, the network size has been reduced by nearly 60%, and the processing speed has been increased by 20%. The image effect after hiding the information was improved, and the PSNR between the secret image and the extracted image was improved by 6.3 dB.

Reversible Data Hiding in a Chaotic Encryption Domain Based on Odevity Verification

On the premise of guaranteeing the visual effect, in order to improve the security of the image containing digital watermarking and restore the carrier image without distortion, reversible data hiding in chaotic encryption domain based on odevity verification was proposed. The original image was scrambled and encrypted by Henon mapping, and the redundancy between the pixels of the encrypted image was lost. Then, the embedding capacity of watermarking can be improved by using odevity verification, and the embedding location of watermarking can be randomly selected by using logistic mapping. When extracting the watermarking, the embedded data was judged according to the odevity of the pixel value of the embedding position of the watermarking, and the carrier image was restored nondestructively by odevity check image. The experimental results show that the peak signal-to-noise ratio (PSNR) of the original image is above 53 decibels after the image is decrypted and restored after embedding the watermarking in the encrypted domain, and the invisibility is good.

Reversible data hiding in chaotic encryption domain based on odevity verification

On the premise of guaranteeing the visual effect, in order to improve the security of the image containing digital watermarking and restore the carrier image without distortion, reversible data hiding in chaotic encryption domain based on odevity verification was proposed. The original image was scrambled and encrypted by Henon mapping, and the redundancy between the pixels of the encrypted image was lost. Then, the embedding capacity of watermarking can be improved by using odevity verification, and the embedding location of watermarking can be randomly selected by using logistic mapping. When extracting the watermarking, the embedded data was judged according to the odevity of the pixel value of the embedding position of the watermarking, and the carrier image was restored nondestructively by odevity check image. The experimental results show that the peak signal-to-noise ratio (PSNR) of the original image is above 53 decibels after the image is decrypted and restored after embedding the watermarking in the encrypted domain, and the invisibility is good.

A Hybrid Digital Image Watermarking Scheme Incorporating DWT, DFT, DCT and SVD Transformations

Digital watermarking provides copyright protection and proof of ownership by inserting watermark metadata as owner’s identity in digital documents to prevent authenticity and copyright violations. The paper introduces a new hybrid image watermarking scheme by attaching multiple copies of watermarks in carrier image. The new scheme utilizes the advantages of DWT, DFT, DCT and SVD transformations to offer stable resistance in protecting watermark contents from various external attacks. The proposed scheme uses Haar wavelet, Fourier, Onion Peel Decomposition, DCT, zigzag ordering and SVD transforms to decompose the carrier image in to four levels to maintain imperceptibility in the watermarked images. The algorithm attaches replicas of watermark frequency blocks in all frequency components of host image to provide better robustness against external deprivations in watermarked images. The proposed algorithm also provides the increased probability of extracting at least one undamaged replica of watermark even when other frequencies are damaged by external attacks. The improved experimental results of the proposed scheme in terms of visual analysis and quantitative metrics on different images with different experimental set up demarcate that the proposed watermarking scheme provides stable performance in generating better watermarked images. It is experimentally found that the new scheme produces high quality watermarked images with an average of 7.62% lesser Mean Absolute Error (MAE) and increased Peak Signal to Noise Ratio (PSNR), Mean Structural Similarity Index Measure (MSSIM) and Feature Similarity Index Measure (FSIM) of 5.02 %, 4.37 %, and 2.37 % respectively than the next best algorithms when simulated with 20 sets of watermark and cover images. The watermark images extracted by the proposed algorithm from extremely distorted watermarked images are with better visual and objective values than other methods used in the comparative study. Simulation analysis on 20 sets of watermark and cover images with 30 types of potential attacks reveals that the extracted watermark images through the proposed scheme produces an average of 5.62%, 6.37%, 5.75% improved Pearson Correlation Coefficients (PCC), Number of Changing Pixel Rate (NPCR) and the Unified Averaged Changed Intensity (UACI) values respectively than the next best algorithms used in the comparative study.

Lossless Watermarking Algorithm Based on Multiple-Base Notational System and Pixel Difference

In order to identify the authenticity of the industrial packaging, the solution to the current watermark technology is mainly to embed the same watermark capacity into each pixel value in the image, so that the watermark capacity is small, and the anti-distortion performance is not good. Data watermarking algorithm based on system and pixel difference. First divide the carrier image into non-overlapping sub-blocks, and calculate the pixel difference of each sub-block; introduce a hybrid system to obtain different bases. According to the pixel difference, the base selection rule is defined; considering the human visual characteristics, the pixel interval adaptive adjustment mechanism is designed to improve the coding technology and complete the watermark information embedding; finally, the watermark information extraction mechanism is established to restore the watermark. The experimental results show that compared with the current data watermarking algorithm, the proposed algorithm has ideal imperceptibility, as well as larger watermark capacity and lower distortion.

Separable Reversible Data Hiding in Encryption Image with Two-Tuples Coding

Separable Reversible Data Hiding in Encryption Image (RDH-EI) has become widely used in clinical and military applications, social cloud and security surveillance in recent years, contributing significantly to preserving the privacy of digital images. Aiming to address the shortcomings of recent works that directed to achieve high embedding rate by compensating image quality, security, reversible and separable properties, we propose a two-tuples coding method by considering the intrinsic adjacent pixels characteristics of the carrier image, which have a high redundancy between high-order bits. Subsequently, we construct RDH-EI scheme by using high-order bits compression, low-order bits combination, vacancy filling, data embedding and pixel diffusion. Unlike the conventional RDH-EI practices, which have suffered from the deterioration of the original image while embedding additional data, the content owner in our scheme generates the embeddable space in advance, thus lessening the risk of image destruction on the data hider side. The experimental results indicate the effectiveness of our scheme. A ratio of 28.91% effectively compressed the carrier images, and the embedding rate increased to 1.753 bpp with a higher image quality, measured in the PSNR of 45.76 dB.

An authentication alternative using histogram shifting steganography method

This study aims to develop an authentication alternative by applying the Histogram shifting steganography method. The media used for authentication is image media. Histogram shifting utilizes the histogram of an image to insert a secret message. The developed authentication has implemented the Histogram shifting to insert user credentials into the carrier image. Users can use the steganographic image to log into their accounts. The method extracts the credentials from the image during the login. PSNR test of the steganographic images produces an average value of 52.52 dB. The extraction capability test shows that the method can extract all test images correctly. In addition, this authentication method is also more resistant to attacks common to password authentication.

Multimedia Communication Security in 5G/6G Coverless Steganography Based on Image Text Semantic Association

Recently, researchers have shown that coverless steganography is relatively safe. On this basis, to improve the payload of the coverless steganography, a novel semiconstruction coverless steganography algorithm is introduced in the paper. Firstly, web crawler technology is applied to crawl a wide range of small icons and hot news images from the Internet. These icons can be used as the training subset, and the hot news can be designed according to construction rules. Secondly, the Alex-Net network is introduced for training in the algorithm, and the adversarial samples are added to the training set. Thirdly, using the preset template, certain small icons and a hot news image are spliced into a secret carrier image according to the construction principle. The hot news image is in the top half of the carrier, and those small icons are in the bottom half. The image on the upper part of the carrier and the icons of the lower part can be connected by image and text semantics, and the semantic matching can be realized between image semantics and explanatory. The experimental results and analysis show that the proposed algorithm can resist steganalysis tools effectively and has good robustness against various image attacks. Meanwhile, the secret information payload has been greatly improved, the maximum payload can reach 180 bits of a single 512 × 512 image. This promising algorithm can be applied to build covert communications.

SteganoCNN: Image Steganography with Generalization Ability Based on Convolutional Neural Network

Image-to-image steganography is hiding one image in another image. However, hiding two secret images into one carrier image is a challenge today. The application of image steganography based on deep learning in real-life is relatively rare. In this paper, a new Steganography Convolution Neural Network (SteganoCNN) model is proposed, which solves the problem of two images embedded in a carrier image and can effectively reconstruct two secret images. SteganoCNN has two modules, an encoding network, and a decoding network, whereas the decoding network includes two extraction networks. First, the entire network is trained end-to-end, the encoding network automatically embeds the secret image into the carrier image, and the decoding network is used to reconstruct two different secret images. The experimental results show that the proposed steganography scheme has a maximum image payload capacity of 47.92 bits per pixel, and at the same time, it can effectively avoid the detection of steganalysis tools while keeping the stego-image undistorted. Meanwhile, StegaoCNN has good generalization capabilities and can realize the steganography of different data types, such as remote sensing images and aerial images.

Secure Data Hiding using Reversible Image Transformation

In today’s era, the large amount of data’s are stored in cloud. But nowadays securely storing data to the cloud is an important task. But the unauthorized parties are tries to decrypt the data from the cloud. So, the data stored in cloud should be secure from any malicious activities. Based on these requests, we propose a framework named reversible data hiding (RDH). It mainly works on encrypted images based on reversible image transformation (RIT). The server insert data into the cloud. On that time, he will add some additional information for the protection of data. In the given framework, the original data can be embedded in another image named carrier image with equal size. So, the hacker tries to pullout the data, he will only get the carrier image. So we can accommodate more data’s into a single storage space. The method picks the data to be hide and a carrier image with equal size. The cover image is embedded into the original image based on the LSB insertion algorithm. i.e., the original data’s are dissolved into the carrier image using a secret hiding key. The cover image is encrypted using blow fish encryption algorithm. It includes normal RDH method and RDH with RIT. Using RIT, it gives high visual quality and security. The technique is mainly used in medical imagery, military imagery for reliable data storage.