In this paper, a new quantum image steganography scheme to embed quantum secrete gray image into quantum cover image is proposed. In the proposed scheme, the quantum secret image scrambled utilizing Arnold cat map and embedding the result into quantum cover image using two least significant qubit (LSQb).The extracting process need only stego image to extract the embedded secret image. The simulation results demonstrate that the proposed scheme has good invisibility and high capacity.
In this paper, a new quantum image steganography scheme to embed quantum secrete gray image into quantum cover image is proposed. In the proposed scheme, the quantum secret image scrambled utilizing Arnold cat map and embedding the result into quantum cover image using two least significant qubit (LSQb).The extracting process need only stego image to extract the embedded secret image. The simulation results demonstrate that the proposed scheme has good invisibility and high capacity.
In quantum image steganography, embedding capacity and security are two important issues. This paper presents a novel quantum steganography scheme using color images as cover images. First, the secret information is divided into 3-bit segments, and then each 3-bit segment is embedded into the LSB of one color pixel in the cover image according to its own value and using Gray code mapping rules. Extraction is the inverse of embedding. We designed the quantum circuits that implement the embedding and extracting process. The simulation results on a classical computer show that the proposed scheme outperforms several other existing schemes in terms of embedding capacity and security.
The concept of Cryptography and Steganography is not a new technique, even though it is ancient but not static. In Cryptography and Steganography the new emerging techniques are done using Quantum Mechanics and Quantum Physics. In this paper, mainly works on how to use Quantum Technique in cryptography system and in field of steganography. Steganography is a process of hiding information of the different types of media files (audio, text, image and video) in another media files. In this paper, mainly the quantum steganography works for two imagery files. The quantum secret image will be hiding in the Quantum Cover image. In this process of hiding of information or image, need to select the pixels. The Qbits used to store the secret image are two most and least significant Qbits. The secret image will be scrambled first, using Arnold’s cat map technique, and then will be embedded into Quantum Cover picture. The Stegno Image is sufficient to extract the secret information. The NEQR quantum representation model is used for converting image into quantum states. The simulation result and analysis demonstrates that the proposed scheme has good visibility and high embedding capacity.
Information hiding aims to embed secret data into the multimedia, such as image, audio, video, and text. In this paper, two new quantum information hiding approaches are put forward. A quantum steganography approach is proposed to hide a quantum secret image into a quantum cover image. The quantum secret image is encrypted first using a controlled-NOT gate to demonstrate the security of the embedded data. The encrypted secret image is embedded into the quantum cover image using the two most and least significant qubits. In addition, a quantum image watermarking approach is presented to hide a quantum watermark gray image into a quantum carrier image. The quantum watermark image, which is scrambled by utilizing Arnold's cat map, is then embedded into the quantum carrier image using the two least and most significant qubits. Only the watermarked image and the key are sufficient to extract the embedded quantum watermark image. The proposed novelty has been illustrated using a scenario of sharing medical imagery between two remote hospitals. The simulation and analysis demonstrate that the two newly proposed approaches have excellent visual quality and high embedding capacity and security.
In this paper, a quantum color image watermarking scheme is proposed through twice-scrambling of Arnold transformations and steganography of least significant bit (LSB). Both carrier image and watermark images are represented by the novel quantum representation of color digital images model (NCQI). The image sizes for carrier and watermark are assumed to be [Formula: see text] and [Formula: see text], respectively. At first, the watermark is scrambled into a disordered form through image preprocessing technique of exchanging the image pixel position and altering the color information based on Arnold transforms, simultaneously. Then, the scrambled watermark with [Formula: see text] image size and 24-qubit grayscale is further expanded to an image with size [Formula: see text] and 6-qubit grayscale using the nearest-neighbor interpolation method. Finally, the scrambled and expanded watermark is embedded into the carrier by steganography of LSB scheme, and a key image with [Formula: see text] size and 3-qubit information is generated at the meantime, which only can use the key image to retrieve the original watermark. The extraction of watermark is the reverse process of embedding, which is achieved by applying a sequence of operations in the reverse order. Simulation-based experimental results involving different carrier and watermark images (i.e. conventional or non-quantum) are simulated based on the classical computer’s MATLAB 2014b software, which illustrates that the present method has a good performance in terms of three items: visual quality, robustness and steganography capacity.
Digital steganography is the art and science of hiding information in covert channels, so as to conceal the information and prevent the detection of hidden messages. On the classic computer, the principle and method of digital steganography has been widely and deeply studied, and has been initially extended to the field of quantum computing. Quantum image steganography is a relatively active branch of quantum image processing, and the main strategy currently used is to modify the LSB of the cover image pixels. For the existing LSB-based quantum image steganography schemes, the embedding capacity is no more than 3 bits per pixel. Therefore, it is meaningful to study how to improve the embedding capacity of quantum image steganography. This work presents a novel steganography using reflected Gray code for color quantum images, and the embedding capacity of this scheme is up to 6 bits per pixel. In proposed scheme, the secret qubit sequence is considered as a sequence of 6-bit segments. For 6 bits in each segment, the first 3 bits are embedded into the second LSB of RGB channels of the cover image, and the remaining 3 bits are embedded into the LSB of RGB channels of the cover image using reflected-Gray code to determine the embedded bit from secret information. Following the transforming rule, the LSBs of stego-image are not always same as the secret bits and the differences are up to almost 50%. Experimental results confirm that the proposed scheme shows good performance and outperforms the previous ones currently found in the literature in terms of embedding capacity.
Embedding secret information into quantum carrier image for covert communication is one of significant research fields of quantum secure communication. Using good imperceptibility and high embedding efficiency of matrix coding, this paper proposes a novel matrix coding-based quantum steganography algorithm for quantum color images. In order to better apply matrix coding in actual demand, two different embedding methods are proposed. One embedding method is single pixel-embedded (1, 3, 2) coding, called SPE (1, 3, 2) coding for short. This method embeds two qubits of secret information into three least significant qubits (LSQbs) of a single pixel of quantum carrier image, and at most only one LSQb would be changed. The other embedding method is the multiple pixels-embedded (1, 3, 2) coding, called MPsE (1, 3, 2) coding, in which three LSQbs of multiple carrier pixels are utilized to embed two secret qubits. On account of experimental simulation obtained in the MATLAB environment, it shows that the new algorithm has good performance in the imperceptibility, the security, the embedding efficiency, and the embedding capacity.