Cheating Immune Block-Based Progressive Visual Cryptography

An advantage of steganography, as opposed to other information hiding techniques, is that the embedder can select a cover image that results in the least detectable stego image. In a previously proposed method, a technique based on block texture similarity was introduced where blocks of cover image were replaced with the similar secret image blocks; then indices of secret image blocks were stored in cover image. In this method, the blocks of secret image are compared with blocks of a set of cover images and the image with most similar blocks to those of the secret image is selected as the best candidate to carry the secret image. Using appropriate features for comparing image blocks, guaranties higher quality of stego images and consequently, allows for higher embedding capacity, less delectability and, enhanced security. Based on this idea, in this paper, an adaptive cover selection steganography method is proposed, that uses statistical features of image blocks and their neighborhood. Using the block neighborhood information, we prevent appearing virtual edges in the sides and corners of the replaced blocks. Our method is examined with feature based and wavelet based steganalysis algorithms. The results prove the effectiveness and benefits of the proposed method.

To compromise between imperceptibility and robustness property of robust image watermarking technique, a RDWT-DCT based blind image watermarking scheme using Arnold scrambling is presented in this paper. Firstly, RDWT (Redundant Discrete Wavelet Transform) is applied to each gray scale cover image block after the image is decomposed into fixed size non overlapping blocks. Secondly, the binary watermark logo is encrypted by Arnold chaotic map and reshaped to a sequence to improve the security of the logo. In the subsequent step, DCT (Discrete Cosine Transform) is employed on each LH subband of the non-overlapping host image block. Finally, after zigzag scanning of each DCT block a binary bit of watermark is embedded into each block by adjusting some middle significant AC coefficients using repetition code. Experimental results show that robustness is achieved by recovering satisfactory watermark data from the reconstructed cover image after applying common geometric transformation attacks (like rotation, cropping, scaling, shearing and deletion of lines or column operation etc.), common enhancement technique attacks (like lowpass filtering, histogram equalization, sharpening, gamma correction, noise addition etc.) and JPEG compression attacks. The proposed scheme is also tested to verify the robustness performance against standard benchmark software "Checkmark" and satisfactory results are achieved against the Checkmark attacks such as Hard and Soft Thresholding, Template Removal, Warping, Dithering, Remodulation and Downsampling/Upsampling etc.

A new secure image transmission technique is proposed, which transforms automatically a given large-volume secret image into a so-called secret-fragment-visible mosaic image of the same size. The mosaic image, which looks similar to an arbitrarily selected target image and may be used as a camouflage of the secret image, is yielded by dividing the secret image into fragments and transforming their color characteristics to be those of the corresponding blocks of the target image. Skillful techniques are designed to conduct the color transformation process so that the secret image may be recovered nearly losslessly. A scheme of handling the overflows/underflows in the converted pixels' color values by recording the color differences in the untransformed color space is also proposed. The information required for recovering the secret image is embedded into the created mosaic image by a lossless data hiding scheme using a key. Good experimental results show the feasibility of the proposed method.

Most of the secret sharing schemes are based on algebraic calculations in their realizations. But there are some different realizations of the secret sharing schemes. Visual cryptography is one such secret sharing scheme. In a visual cryptographic scheme, for a set P of n participants, a secret image is split into n shadow images called shares, where each participant in P receives one share. Certain qualified subsets of participants can ldquovisuallyrdquo recover the secret image with some loss of contrast, but other forbidden sets of participants have no information about the secret image. In this paper we review with appropriate examples some of the methods for the construction of monochrome visual cryptographic schemes for general as well as for threshold access structures.

Visual cryptography (VC) schemes provide a distinguished image encryption technique to protect image security since it can visually decrypt the secret image by superimposing the encrypted shadows. VC schemes for both threshold access structures and general access structures are generally constructed based on the OR operation to minimize the pixel expansion. However, VC schemes with optimal pixel expansion typically have low contrast. Stacking operation OR frequently produces recovered images with poor visual quality and are never able to deliver flawless recovery for secret images. Therefore, we studied XOR-based VC (XVC) schemes that employ linear programming to maximize their contrast. Three schemes for general access structures and three schemes for threshold access structures are designed to maximize their contrast. The proposed schemes’ construction is reduced to a linear programming to maximize the contrast by determining the ideal combinations of basis matrices in terms of primary column matrices and unit matrices, respectively. The comparison study and experimental results demonstrate that the contrast of the previous VC and XVC schemes can be further improved.

Traditional k out of n visual cryptography scheme has been proposed to encrypt single secret image into n shares where only k or more shares can decode the secret image. Many existing schemes on visual cryptography are restricted to consider only binary images as secret which are not appropriate for many important applications. Store-and-Forward telemedicine is one such application where medical images are transmitted from one site to another via electronic medium to analyze the patient's clinical health status. The main objective of Store-and-Forward telemedicine is to provide remote clinical services via two-way communication between the patient and the healthcare provider using electronic medical image, audio and video means. In this paper, a new XOR based Continuous-tone Multi Secret Sharing scheme suitable for store-and-forward telemedicine is proposed to securely transmit the medical images. It also eliminates basic security constraints of VC like pixel expansion in shares/recovered secret images, random pattern of shares, explicit codebook requirement, lossy recovery of secret and limitation on number of secret and shares. Proposed approach is n out of n multi secret sharing scheme which is able to transmit n secret images simultaneously. All secrets could be revealed only after some computations with all n shares and one master share. Master share has been created with the secret key at encoding phase and it can be regenerated at the time of decoding using same secret key. Here all shares are meaningful in continuous-tone which may provide confidentiality to medical images during transmission. Proposed approach not only preserves all basic characteristics of traditional VC but also increases the capacity of secret image sharing. From the experiments we found that irrespective of visible contents of the shares, the probability of getting back the pixel values of respective original secret images at the receiver end is very high.

A hybrid approach combining data hiding with visual cryptography for secure extraction of data hiding

Steganography is the art of hiding secret data in a medium whereas visual-cryptography is a cryptographic technique where a full image is encrypted. The security of image steganography depends on the secret key set which is used for embedding the secret image. If the secret key is exposed, the secret image can be retrieved. To solve this security issue we propose a new type of steganography method using visual cryptography. In this method, text and image are used as a secret message and image for the cover object. 24-bit RGB color images are used as both secret and cover images. In this method, we use a new image namely share1 which converts a secret image to a totally different image called share2 image. Typically, knowing the extraction method, people can retrieve the secret message easily. A pseudorandomly generated image is used as a key for visual encryption and this ensures the extra layer of security. By this proposed method, we ensure more secured image steganography.

Objective: For reducing the data redundancy to save more hardware space and transmission bandwidth, data compression is used. Methods: For image compression, we have proposed a new method based on c-mean and absolute moment Block Truncation Coding (BTC) techniques. In this technique an image is segmented into several non-overlapping blocks. For each block, calculate the weighted c-mean by means of linear combination of its arithmetic mean and c-mean. The c-mean is evaluated by expressing every pixel into a sum of largest perfect square of non-negative integer. For each image block, the pixels are classified into two range of values based on weighted c-mean. The gray values of the image block which are greater than block weighted c-mean are considered as upper range and otherwise lower range. The weighted c-mean of upper range and lower range are termed as higher c-mean and lower c-mean respectively. Then construct the binary block matrix (0/1) based on weighted c-mean as a quantization level. In the decoder part, an image block is reconstructed by replacing the 1's with upper c-mean and 0's by lower c-mean of block matrix. Findings: The newly designed method is tested some8-bit standard images. It is also compared with related works in term of Peak Signal to Noise Ratio, Bit Rate, and Structural similarity index. It shows the effectiveness of the proposed method. Applications: Image storage is required for several purposes like document, medical images, magnetic resonance imaging and radiology, motion pictures etc. All such applications are based on image compression.

Hiding the data in digital images has been area of interest in the digital image processing domain. Although so much work has been carried out in the literature to resolve the issues like increasing the data capacity, creating the secret image alike of target image but most of the works fails to meet the practical requirements. This paper presents an approach where mosaic image generation has done by dividing the secret image into fragments and transforming their respective colour characteristics into corresponding blocks of the target image. Usage of the Pixel colour transformations helps to yield the lossless recovered image based on the untransformed colour space values. Generation of the key plays an important role to recover the data from the secret image in lossless manner. Finally the same approach can be performed on videos also which helps to eliminate the flickering artifact to achieve the lossless data recovery in motion related videos. The experimental results shows good robust behavior against all incidental and accidental attacks and compare to the conventional algorithms performance evaluation has been increased in a significant way. The result of the proposed technique outperforms present techniques and the results are simulated using MATLAB.

Visual Cryptography for General Access Structures

In this paper, we propose a security-enhanced method for the visual cryptography schemes using recursion. Visual cryptography is interesting because decryption can be done with no prior knowledge of cryptography and can be performed without any cryptographic computations. The proposed method, the secret image is encoded into shares and subshares in a recursive way. By using recursion for the visual cryptography schemes, the security and reliability of the secret image can be improved than in the case of existing visual cryptography schemes.

Since visual cryptography scheme (VCS) was introduced by Naor and Shamir, contrast has been always regarded as an evaluation standard of visual quality of the revealed secret image. However, its original definition only reflects the relative difference between white area and black area of the revealed secret image so that it is incapable to access actual visual quality. Although other definitions of contrast were also proposed, researchers have not reached consensus on the definition of contrast until now. In this paper, a novel method is proposed to obtain recognition result of the revealed character secret image through simulating the recognition procedure of our human eyes. Recognition rate is adopted to evaluate the clearness of the revealed secret image. Experimental results and comparisons demonstrate that recognition rate can be regarded as a new visual evaluation criterion of VCS for character secret image. Finally, a construction of VCS with optimized overall pixel expansion is provided, in which the pixel expansion is thoroughly determined by recognition rate, rather than contrast.

Content-based image quality metric using similarity measure of moment vectors

In this paper, an experimental analysis and study of the Modified Signed-Digit (MSD) method was conducted, which aims to hide a quantity of secret data represented in a grayscale image of size 512 × 512 in a set of cover images. Some quality metrics such as signal-to-noise ratio (PSNR), mean squared error (MSE), and embedding capacity (BPP) were measured. As well as calculating, the optimal number of cover images, the time taken in the hiding process, and the consumed memory. The experiments were conducted two different sizes of cover images, where the number of cover images required for the secret image is determined according to some inputs such as the number of pixels n in each group of the cover image and the number of bits in each block of the secret image L=n+1. Also, four different values of n, (2, 3, 4, 5). We tried to find the best value for the number of bits in each block L of the secret image and in each case of n to achieve the best case for image quality PSNR, MSE for both cover image sizes, and on the other hand, less time memory consumption. By using the Matlab program, we compared the results at different cover image sizes, we found that as the larger size used, the fewer cover images are needed and less time consumption. On the other hand, more memory consumption. For the other metrics, PSNR, MSE and BPP, close results were obtained. Finally, the best choice remains related to the user and the type of application or the required performance, whether in image quality or in less memory and time consumption with a larger embedding capacity. Keywords: MSD algorithm, Signal-to-noise ratio (PSNR), Mean square error (MSE), Bit-per-pixel (BPP), Memory consumption, Time consumption.