Data In Least Significant Bit Research Articles

Secure Reversible Data Hiding in Encrypted Image Based on 2D Labeling and Block Classification Coding

The existing lossless compression methods in reversible data hiding in encrypted images (RDHEI) do not fully utilize pixel and local redundancy, and encryption methods can not resist various attack algorithms. To solve the above problem, a secure RDHEI algorithm based on 2D labeling and block classification coding is proposed. In the proposed RDHEI algorithm, the retained total LSB (least significant bit) data as the image feature in the mixed permutation to generate the encryption key that varied with image, which improves the security of the algorithm. In addition, 2D labeling and block classification coding are designed. The former improves the utilization of pixel redundancy by labeling the length of the first ‘0’ string and the next ‘1’ string in the predicted value. The latter effectively utilizes the local correlation of the image, reduces the number of label values in the smooth block, so the length of the compressed coding stream is reduced. The combination of 2D labeling and block classification coding effectively improves the capacity. Experimental results show that the proposed method can effectively resist statistical, known plaintext and differential attacks, and the average capacity of three databases is 0.41bpp higher than the state-of-the-art algorithms.

Viewing Direction Based LSB Data Hiding in 360° Videos

In this paper, we propose a viewing direction based least significant bit (LSB) data hiding method for 360° videos. The distributions of viewing direction frequency for latitude and longitude are used to control the amount of secret data to be hidden at the latitude, longitude, or both latitude and longitude of 360° videos. Normalized Gaussian mixture models mimicking the viewing behavior of humans are formulated to define data hiding weight functions for latitude, longitude, and both latitude and longitude. On this basis, analytical expressions for the capacity offered by the proposed method to hide secret data in 360° cover videos are derived. Numerical results for the capacity using different numbers of bit planes and popular 360° video resolutions for data hiding are provided. The fidelity of the proposed method is assessed in terms of the peak signal-to-noise ratio (PSNR), weighted-to-spherically uniform PSNR (WS-PSNR), and non-content-based perceptual PSNR (NCP-PSNR). The experimental results illustrate that NCP-PSNR returns the highest fidelity because it gives lower weights to the impact of LSB data hiding on fidelity outside the front regions near the equator. The visual quality of the proposed method as perceived by humans is assessed using the structural similarity (SSIM) index and the non-content-based perceptual SSIM (NCP-SSIM) index. The experimental results show that both SSIM-based metrics are able to account for the spatial perceptual information of different scenes while the PSNR-based fidelity metrics cannot exploit this information. Furthermore, NCP-SSIM reflects much better the impact of the proposed method on visual quality with respect to viewing directions compared to SSIM.

Data hiding in digital images using a partial optimization technique based on the classical LSB method

This paper presents a new partial optimization approach for the least significant bit (LSB) data hiding technique that can be used for protecting any secret information or data. A deterioration effect of as little as possible in an image is intended using the LSB data hiding technique and this is well realized utilizing the proposed partial optimization approach achieving the same data embedding bit rates. In the proposed approach, all of the image pixels are classified into 8 regions and then the 8 distinct ordering codings are applied to each region by the developed partial optimization encoder. Thus, the most effective outcome that has been obtained from the 8 regions means that the number of the altered bits is kept minimized. Hence, the minimal values that have been attained from the 8 regions enable decoding that ensures relatively small distortions on the extracted cover image.

Transforming LSB Substitution for Image-based Steganography in Matching Algorithms

Simple least-significant-bit (LSB) substitution is a method used to embed secret data in least significant bits of pixels in a host image. The LSB approaches typically achieve high capacity. A simple LSB substitution, which hides secret data directly into LSBs, is easily implemented but will result in bad quality of the stego-image. In order to reduce the degradation of the host image after embedding, an LSB substitution scheme was proposed by Wang et al. They proposed a genetic algorithm to search for approximate solutions. Also, Chang et al. proposed a dynamic programming strategy to efficiently obtain a solution. In this paper, we propose a more general model of Wang et al.'s LSB substitution scheme, called as transforming LSB substitution. In order to overcome the problem associated with the two previous approaches of a long running time, a more efficient approach, referred to as the matching approach, is proposed to find a better solution. Some experiments, demonstrations and analyses are shown in this paper to demonstrate our new scheme and approach.

A least-significant-bit substitution data hiding scheme by using modulus function and optimal permutation refining

Least significant bit (LSB) substitution is one of the most straight and simple technique to hide data hiding in an image. It has been widely used in steganography, watermarking, data compression, and so on. So far, there have been many developments to improve the quality of the embedded images such like genetic algorithm, dynamic programming, modulus functions, etc. To further improve LSB data hiding, an adapted LSB data hiding scheme by using modulus function and optimal permutation search is provided in this paper. The paper presents an LSB-based data hiding scheme by using modulus function and optimal permutation refining. The proposed scheme has higher PSNR values of stego-images in the same capacity that can raise the efficiency of current data hiding schemes and can be used in wide applications.

Real-time digital error correction for flash analog-to-digital converter

We have designed, fabricated and successfully tested digital error-correction circuits to improve the performance of superconductive flash analog-to-digital converters (ADCs). The comparators coding the most significant bits (MSBs) are the least sensitive to the input signal, and therefore have the most threshold errors due to jitter and threshold misplacement. These errors are completely eliminated by implementing an ADC architecture using two comparators per bit, and employing logic to encode bit N by looking back to the state of the (N-1) bit. In this way, all code transitions are derived from the least significant bit (LSB) comparators. The MSB comparators are used only to encode the LSB data.

Real-time digital error correction for flash analog-to-digital converter

We have designed, fabricated and successfully tested digital error-correction circuits to improve the performance of superconductive flash analog-to-digital converters (ADCs). The comparators coding the most significant bits (MSBs) are the least sensitive to the input signal, and therefore have the most threshold errors due to jitter and threshold misplacement. These errors are completely eliminated by implementing an ADC architecture using two comparators per bit, and employing logic to encode bit N by looking back to the state of the (N-1) bit. In this way, all code transitions are derived from the least significant bit (LSB) comparators. The MSB comparators are used only to encode the LSB data.