A Novel LSB Matching Algorithm Based on Information Pre-Processing

This paper analyzes random bits and scanned documents, two forms of secret data. The secret data were pre-processed by halftone, quadtree, and S-Box transformations, and the size of the scanned document was reduced by 8.11 times. A novel LSB matching algorithm with low distortion was proposed for the embedding step. The golden ratio was firstly applied to find the optimal embedding position and was used to design the matching function. Both theory and experiment have demonstrated that our study presented a good trade-off between high capacity and low distortion and is superior to other related schemes.

A New Digital Image Steganography Based on Center Embedded Pixel Positioning

In this study we propose a new approach to tackle the cropping problem in steganography which is called Center Embedded Pixel Positioning (CEPP) which is based on Least Significant Bit (LSB) Matching by setting the secret image in the center of the cover image. The evaluation of the experiment indicated that the secret image can be retrieved by a maximum of total 40% sequential cropping on the left, right, up, and bottom of the cover image. The secret image also can be retrieved if the total asymmetric cropping area is 25% that covered two sides (either left-right, left-up or right-up). In addition, the secret image can also be retrieved if the total asymmetric cropping area is 70% if the bottom part is included. If asymmetric cropping area included three sides, then the algorithm fails to retrieve the secret image. For cropping in the botom the secret image can be extracted up to 70%.

Improving the Reversible LSB Matching Scheme Based on the Likelihood Re-encoding Strategy

In 2018, Tseng et al. proposed a dual-image reversible embedding method based on the modified Least Significant Bit matching (LSB matching) method. This method improved on the dual-image LSB matching method proposed by Lu et al. In Lu et al.’s scheme, there are seven situations that cannot be restored and need to be modified. Furthermore, the scheme uses two pixels to conceal four secret bits. The maximum modification of each pixel, in Lu et al.’s scheme, is two. To decrease the modification, Tseng et al. use one pixel to embed two secret bits and allow the maximum modification to decrease from two to one such that the image quality can be improved. This study enhances Tseng et al.’s method by re-encoding the modified rule table based on the probability of each hiding combination. The scheme analyzes the frequency occurrence of each combination and sets the lowest modified codes to the highest frequency case to significantly reduce the amount of modification. Experimental results show that better image quality is obtained using our method under the same amount of hiding payload.

A New Method of Coding for Steganography Based on LSB Matching Revisited

LSB matching revisited is an LSB-based approach for image steganography. This method is a type of coding to increase the capacity of steganography. In this method, two bits of the secret message are hidden in two pixels with only one change. But this method provides no idea for hiding a message with a large number of bits. In other words, this method works only for n = 2 , where n is the number of bits in a block of the secret message. In this paper, we propose an improved version of the LSB matching revisited approach, which works for n > 2 . The proposed scheme contains two phases including embedding and extracting the message. In the embedding phase, we first convert the secret message into a bit-stream, and then the bit-stream is divided into a set of blocks including n bits in each block. Then we choose 2 n − 1 pixels for hiding such n bits of the secret message. In the next step, we choose the operations needed to generate such a message. Finally, we perform the obtained operations over the coefficients to hide the secret message. The proposed approach needs fewer changes than LSB MR when n > 2 . The capacity of the proposed approach is 2 n − 1 / 2 n − 1 − 1 × 100 % higher than the F5 method where this value for n > 2 is bigger than 75%. For example, the capacity of our scheme is 75% higher than the capacity of F5 for n = 3 . The proposed method can be used in the first step of every steganography method to reduce the change in the stego image. Therefore, this method is a new coding method for steganography. Our experimental results using steganalysis show that using our method provides around 10% higher detection error for SRNet over two steganography schemes.

Indiscernibility Mask Key for Image Steganography

Our concern in this paper is to explore the possibility of using rough inclusions for image steganography. We present our initial research using indiscernibility relation as a steganographic key for hiding information into the stego carrier by means of a fixed mask. The information can be embedded into the stego-carrier in a semi-random way, whereas the reconstruction is performed in a deterministic way. The information shall be placed in selected bytes, which are indiscernible with the mask to a fixed degree. The bits indiscernible with other ratios (smaller or greater) form random gaps that lead to somehow unpredictable hiding of information presence. We assume that in our technique it can modify bits, the change of which does not cause a visual modification detectable by human sight, so we do not limit ourselves to the least significant bit. The only assumption is that we do not use the position when the mask we define uses it. For simplicity’s sake, in this work we present its operation, features, using the Least Significant Bit (LSB) method. In the experimental part, we have implemented our method in the context of hiding image into the image. The LSB technique in its simplest form is not resistant to stegoanalisys, so we used the well-known LSB matching method to mask the presence of our steganographic key usage. To verify the resistance to stegoanalisys we have conducted and discussed Chi-square and LSB enhancement test. The positive features of our method include its simplicity and speed, to decode a message we need to hide, or pass to another channel, a several-bit mask, degree of indiscernibility and size of the hidden file. We hope that our method will find application in the art of creating steganographic keys.