Abstract
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.
Highlights
Us, an information-hiding technique must declare its main objective to improve some of these parameters
Image steganography methods can be divided based on their context into two groups: those in the Spatial Domain and those in the Transform Domain. e spatial domain steganography methods change some bits of the pixels in the cover image. e pixels employed for hiding the secret data are selected using a simple and random method. us, these methods provide insufficient robustness. e transform domain steganography methods hide the secret data within the transform coefficients of the cover image. ey use various transforms such as Discrete Cosine Transform (DCT), Discrete Fourier Transform, and Discrete Wavelet Transform [10]. ese methods provide a high level of robustness and low capacity
To address the abovementioned challenge, in this paper, we propose a method that works for n > 2, called here the Advanced LSB MR. e proposed method is a new method of coding for steganography and can be used in the first step of every steganography method to reduce the change in the stego image
Summary
Us, an information-hiding technique must declare its main objective to improve some of these parameters. Both LSBM and LSBR choose the pixels independently, LSB MR considers every two continuous pixels in a single group In this method, two bits of the secret message are hidden in two pixels with only one change. In LSB, the first pixel is used to hide the first bit of the secret message, and the second bit of the message is hidden based on the even or odd relationship between two pixels of the cover image [12]. This method has no idea for hiding a message with a large number of bits. This method works only for n 2. erefore, it is not possible to accurately compare the capacity of the proposed method with the LSB MR method
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