An Embedding Strategy Using Q-Ary Convolutional Codes for Large and Small Payloads

Matrix embedding (ME) code is a commonly used steganography technique, which uses linear block codes to improve embedding efficiency. However, its main disadvantage is the inability to perform maximum likelihood decoding due to the high complexity of decoding large ME codes. As such, it is difficult to improve the embedding efficiency. The proposed q-ary embedding code can provide excellent embedding efficiency and is suitable for various embedding rates (large and small payloads). This article discusses that by using perforation technology, a convolutional code with a high embedding rate can be easily converted into a convolutional code with a low embedding rate. By keeping the embedding rate of the (2, 1) convolutional code unchanged, convolutional codes with different embedding rates can be designed through puncturing.

A Dynamic Steganography Method for Web Images with Average Run-Length-Coding

Web page has many redundancies, especially the dynamic html multimedia object. This paper proposes a novel method to employ the commonly used image elements on web pages. Due to the various types of image format and complexity of image contents and their position information, secret message bits could be coded to embed in these complex redundancies. Together with a specific covering code called average run-length-coding, the embedding efficiency could be reduced to a low level and the resulting capacity outperforms traditional content-based image steganography, which modifies the image data itself and causes a real image quality degradation. Our experiment result demonstrates that the proposed method has limited processing latency and high embedding capacity. What’s more, this method has a low algorithm complexity and less image quality distortion compared with existing steganography methods.

Block-Based Steganography Method Using Optimal Selection to Reach High Efficiency and Capacity for Palette Images

The primary goal of steganographic methods is to develop statically undetectable methods with high steganographic capacity. The embedding efficiency is one kind of measure for undetectability. Block-based steganography methods have been proposed for achieving higher embedding efficiency under limited embedding capacity. However, in these methods, some blocks with larger embedding distortions are skipped, and a location map is usually incorporated into these methods to record the embedding status of each block. This reduces the embedding capacity for secret messages. In this study, we proposed a block-based steganography method without a location map for palette images. In this method, multiple secret bits can be embedded in a block by modifying at most one pixel with minimal embedding distortion; this enables each block to be used for data embedding; thus, our method provides higher embedding capacity. Furthermore, under the same capacity, the estimated and experimental embedding efficiencies of the proposed method are compared with those of Imaizumi et al. and Aryal et al.’s methods; the comparisons indicate that the proposed method has higher embedding efficiency than Imaizumi et al. and Aryal et al.’s methods.

A Reversible High-Capacity Data Hide System Based on Powerful MSB Prediction in Encrypted Images

For encrypted images (RDHEI) reversible data shielding is an important technique for embedding data into the encrypted domain. A hidden key encrypts an original picture, and additional information may be inserted into the encrypted image during or after transmission without knowing the crypting key or the original contents of the picture. The hidden message can be retrieved during the decoding process and the original image can be restored. RDHEI has begun to generate academic attention over the past couple of years. Data privacy has become a real issue with the growth of cloud computing. None of the current methods, however, will allow us to hide a great deal of information reversibly. In this document we propose a new reversible approach with a very high capacity based on MSB (most important bit) forecasting. We present two approaches: a reversible high-capacity data hiding approach with a prediction-correction error (CPEHCRDH) and an integrated-prediction error (EPE-HCRDH) reversible data hiding approach. With this approach, our findings are better than those achieved with the existing state-of-the-art approaches, both in terms of image quality recovered and embedding efficiency.

Two-Dimensional Histogram Shifting-Based Reversible Data Hiding for H.264/AVC Video

Histogram shifting (HS) has been proved to be a great success in reversible data hiding (RDH). To reduce the quality loss of marked media and the increase in file size, several two-dimensional (2D) HS schemes based on the characteristics of cover media have been proposed recently. However, our analysis shows that the embedding strategies used in these methods can be further optimized. In this paper, two new 2D HS schemes for RDH in H.264/AVC video are developed, one of which uses the DCT coefficient pairs with both values 0 and the other does not. The embedding efficiency of a DCT coefficient pair in different embedding modes is firstly calculated. Then, based on the obtained embedding efficiency along with the statistical distribution of DCT coefficient pairs, two better embedding strategies are proposed. The secret data is finally embedded into the pairs of DCT coefficients of the middle and high frequencies using our proposed strategies. The comparison experiment results demonstrate that our schemes can achieve enhanced visual quality in terms of PSNR, SSIM, and entropy in most cases, and the increase in file size is smaller.

An Efficient Data-Hiding Scheme Based on Multidimensional Mini-SuDoKu

The massive Internet of Things (IoT) connecting various types of intelligent sensors for goods tracking in logistics, environmental monitoring and smart grid management is a crucial future ICT. High-end security and low power consumption are major requirements in scaling up the IoT. In this research, we propose an efficient data-hiding scheme to deal with the security problems and power saving issues of multimedia communication among IoT devises. Data hiding is the practice of hiding secret data into cover images in order to conceal and prevent secret data from being intercepted by malicious attackers. One of the established research streams of data-hiding methods is based on reference matrices (RM). In this study, we propose an efficient data-hiding scheme based on multidimensional mini-SuDoKu RM. The proposed RM possesses high complexity and can effectively improve the security of data hiding. In addition, this study also defines a range locator function which can significantly improve the embedding efficiency of multidimensional RM. Experimental results show that our data-hiding scheme can not only obtain better image quality, but also achieve higher embedding capacity than other related schemes.