4-P Secret Sharing Scheme Deepa Bajaj 1, Navneet Verma 2 1 Master s in Technology (Dept. of CSE), 2 Assistant Professr (Dept. of CSE) 1 er.deepabajaj@gmail.com, 2 navneetcse@geeta.edu.in Geeta Engineering College Panipat, Haryana (India) Abstract: Visual cryptography is one of the techniques used to encrypt the images by dividing the original image into multiple images. The multiple images can be sent to the destination though multiple paths, and at the destination, these images can be combined to get the original image. The proposed work on Visual cryptography provides the demonstration to the users to show how encryption and decryption can be done to the images. Visual cryptography, an emerging cryptography technology, uses the characteristics of human vision to decrypt encrypted images. It needs neither cryptography knowledge nor complex computation. For security concerns, it also ensures that hackers cannot perceive any clues about a secret image from individual cover images. Keywords: Visual cryptography, secret sharing, halftone, Visual Secret Sharing. 1. INTRODUCTION The process of Visual Cryptography, as developed through the original algorithm [1, 2] was designed to be used with binary images. This is illustrated from the nature of the shares and the encryption process documented previously. If the secret messages being encoded contain text or binary images, the process shown in the original algorithm works well. However, the world is not composed of solely black and white pixels. With the increasing production of images in the digital age, gray and color images have a pressing need for encryption and protection as much, or more, as binary images. 1.1 Gray Images: While Naor and Shamir did focus most of their paper on the development of an algorithm to encrypt binary images, they were also aware of the eventual need to encrypt gray and color images. In the last section of their paper, they proposed a technique which involved printing each of the pixels in an image as half black - half white circles. This allowed the rotation angle of the corresponding circles to vary and which would reveal a range of gray tones throughout the overlapped shares. If the rotation angle of the first share pixels are chosen at random, then the relative change in rotation of the corresponding share pixels would result in uniformly gray shares with no information about the original image being revealed [1-3]. An example of this process is shown in Figure 1 which illustrates the overlapping circle pixels process. Not much analysis or mathematical proof is shown, but conceptually the process is valid and will result in two seemingly random shares, that when overlaid perfectly reveal the secret message. While this process has not been popular for encrypting gray images, there has been growing research on other techniques that have gained popularity and success amongst the Visual Cryptography community. One of the more popular methods has implemented the process of halftoning images [4]. Halftoning can be accomplished by thresholding the image. This is done by designating a pixel cut-off value to determine if a gray pixel should be assigned to a black or white pixel. One technique is assigning all gray values below 128 digital counts to black and any above that threshold to white. This results in an image with false shadowing and a mediocre representation of the gray image. Another technique is to examine a subgroup of pixels, determine their average, and reassign that block of pixels with a designated ratio of black and white pixels approximating that level of gray. The number of gray levels used determines the quality of the resulting black and white (gray) image. Figure 1: Visual Cryptography Scheme for Gray Images Using Circle Pixels [1] To illustrate, Figure 2 shows the original image of Lena and corresponding thresholded images using two, eight, and sixteen gray levels, respectively. When compared to the original image, the two gray level images show the overall shape of the image and major features but does not show any of the corner details. The eight gray level image shows more detail than the two level image but still blurs some of the edges and gives false shadows. Of the three thresholded images, the sixteen gray levels is the best representation of the original image, with the note that the possible number of image levels ranges from 2 to 256. The thresholding process results in a choice. Either the image is quickly processed through a minimum number of levels and results in a fair loss of contrast or the processing takes additional time with a larger number of levels and results in an image more representative of the original image. Secret images are divided into share images which, on their own, reveal no information of the original secret. Shares may be distributed to various parties so that only by collaborating with an appropriate number of other parties, can the resulting combined shares reveal the secret image. Recovery of the secret can be done by super imposing the share images and, hence, the decoding process requires no special hardware or software and can be simply done by the human eye. Page 55
Figure 2: Shares of Binary Image Generated with Original Visual Cryptography Algorithm Visual cryptography is of particular interest for security applications based on biometrics [2]. For example, biometric information in the form of facial, fingerprint and signature images can be kept secret by partitioning into shares, which can be distributed for safety to a number of parties. The secret image can then recovered when all parties release their share images which are then recombined. A basic 2-out-of-2 or (2; 2) visual cryptography scheme produces 2 share images from an original image and must stack both shares to reproduce the original image. More generally, a (k; n) scheme produces n shares, but only requires combining k shares to recover the secret image. To preserve the aspect ratio for the recovered secret image for a (2; 2) scheme each pixel in the original image can be replaced in the share images by a 2X2 block of sub-pixels. As shown in Table 1, if the original pixel is white, one of six combinations of share pixels is randomly created. Similarly, the possible share combination for black pixels is also shown. After stacking the shares with white transparent and black opaque, the original secret image will be revealed. Stacking can be viewed as mathematically O Ring, where white is equivalent to 0 and black is equivalent to 1. Table 1: Illustration of a (2; 2) VC Scheme with 4 Subpixels Page 56 2. RELATED WORK In this paper an (n, n) visual cryptography scheme without dithering is proposed. This scheme takes n gray-scale input images to cover a target image across n gray-scale images and produces n gray-scale output images which are very close to the input images, respectively. Since the output images are visibly innocuous and natural, it may be easy to pass visual inspection, which is a very desirable property in terms of the steganography aspect [1]. This method is different from the existing schemes from the fact that it keeps the input images almost intact. In this paper a new (n, n) visual cryptography scheme without dithering is proposed. In this paper a new construction algorithm of visual cryptography is presented. First, the author s extend SFCOD (Space Filling Curve Ordered Dither - one of the techniques of half toning) to transform a gray-level image into an image with fewer gray-scale values. In addition, the author s extend the basic visual cryptography model to handle more than two gray-scale values. Then the extended visual cryptography model can be applied to encode this image. This scheme satisfies the security and contrast conditions [2]. It can reveal more details of original images in the decoded images than ordinary visual cryptography scheme. Preserving the privacy of digital biometric data (e.g. face images) stored in a central database has become of paramount importance. This work explores the possibility of using visual cryptography for imparting privacy to biometric data such as fingerprint images, iris codes, and face images. The proposed algorithm selects the host images that are most likely to be compatible with the secret image based on geometry and appearance. GEVCS is then used to encrypt the private image in the selected host images. It is observed that the reconstructed images are similar to original private image [3]. In this paper, the authors have extended traditional visual secret sharing by introducing a novel (2, 2) VSS scheme without size expansion. The principle of this scheme is to encode a secret block with four pixels into two share blocks according to the number and distribution of black and white pixels, thereby allowing the secret image to be clearly restored by using XOR operation. Our novel scheme can be applied on both binary and halftone images and does not increase the number of pixels required to represent the shares or the recovered image. Although the scheme introduces some noise into the recovered image, the recovered image is substantially clearer than in other proposed non-expansion schemes [4]. A (k, n) visual cryptographic scheme (VCS) encodes a secret image into n shadow images (printed on transparencies) distributed among n participants. When any k participants superimpose their transparencies on an overhead projector (OR operation), the secret image can be visually revealed by a human visual system without computation. However, the monotone property of OR operation degrades the visual quality of reconstructed image for OR-based VCS (OVCS). Accordingly, XOR-based VCS (XVCS), which uses XOR operation for decoding, was proposed to enhance the contrast. In this paper, the author s investigate the relation between OVCS and XVCS. Our main contribution is to theoretically
prove that the basis matrices of (k, n)-ovcs can be used in (k, n)-xvcs. Meantime, contrast is enhanced 2(k 1) times [5]. This study discusses a random-grid-based non-expanded visual cryptography scheme for generating both meaningful and noise-like shares. First, the distribution of black pixels on the share-images and the stack-image is analyzed. A probability allocation method is then proposed which is capable of producing the best contrast in both of the shareimages and the stack-image. With our method, not only can different cover images be used to hide the secret image, but the contrast can be set as needed [6]. The visual cryptography scheme (VCS) is an encryption technique that utilizes the human visual system in recovering a secret image and it does not require any complex calculation. However, the contrast of the reconstructed image could be quite low. A number of reversing-based VCSs (or VCSs with reversing)(rvcs) have been proposed for binary secret images, allowing participants to perform a reversing operation on shares (or shadows).this reversing operation can be easily implemented by current copy machines. The proposed schemes can satisfy different user requirements; previous RVCSs for binary images can be viewed as special cases in the schemes proposed [7]. The proposed (n, n) - NVSS scheme can share one digital secret image over n + 1 arbitrary selected natural images (called natural shares) and one noise-like share. The natural shares can be photos or hand-painted pictures in digital form or in printed form. The noise-like share is generated based on these natural shares and the secret image. The unaltered natural shares are diverse and innocuous, thus greatly reducing the transmission risk problem. The author s also propose possible ways to hide the noise like share to reduce the transmission risk problem for the share [8]. 4. IMPLEMENTATION and RESULTS For implementation purpose, we have use MATLAB 2013. We have taken a secret image as shown in figure 3. By applying above algorithm or methodology, we have generated two parts of the secret image as shown in figure 4 and figure 5. And finally, by combining these two parts we have figure 6 as output. We can observe from figure 6 that the resolution of overlapped image is same as secret image. Hence, our scheme has shown less pixel expansion which is desirable and good for the final retrieval of the secret image. Figure 3: Secret Image Figure 4: Part 1 of Secret Image Figure 5: Part 2 of Secret Image 3. METHODOLOGY 1. Input binary secret image. 2. Divide the image into two parts according to black and white pixels. The steps involved in this process are: i. Transform the gray-level image into a black-andwhite halftone image. ii. For each black or white pixel in the halftone image, decompose it into a 2 2 block of the two transparencies. iii. If the pixel is white, randomly select one combination from the former two rows as the content of blocks in Shares 1 and 2. iv. If the pixel is black, randomly select one combination from the latter two rows as the content of the blocks in the two transparencies. v. Repeat Step 2 until every pixel in the halftone image is decomposed, hence resulting in two transparencies of visual cryptography to share the secret image. 3. Now, Image is divided in to two parts. 4. Both these parts further divided into two subparts. 5. Overlapping of these four sub-parts using XOR gate to generate secret image. Figure 6: Overlapped image by combining part 1 and part 2 We have taken another secret image as shown in figure 7. By applying above algorithm or methodology, we have generated two parts of the secret image as shown in figure 8 and figure 9. And finally, by combining these two parts we have figure 10 as output. We can observe from figure 8 that the resolution of overlapped image is same as secret image. Hence, our scheme has shown less pixel expansion which is desirable and good for the final retrieval of the secret image. Figure 7: Secret Image Page 57
Figure 8: Part 1 of Secret Image Figure 9: Part 2 of Secret Image Figure 16: Part 2 of 1 of Secret Image Figure 10: Overlapped image by combining part 1 and part 2 Figure 17: Part 2 of 2 of Secret Image Figure 11: Secret Image Figure 12: Part 1 of Secret Image Figure 13: Part 2 of Secret Image Figure 14: Part 1 of 1 of Secret Image Figure 15: Part 1 of 2 of Secret Image Figure 18: Image after combining all four parts Here, figure 11 is original image, which is partitioned in to two images figure 12 and figure 13, now each of them is partitioned in two parts as shown in Figure 14 (Part 1 of 1 of Secret Image), Figure 15(Part 1 of 2 of Secret Image), Figure 16 (Part 2 of 1 of Secret Image) and Figure 17 (Part 2 of 2 of Secret Image) and after combining all these four images we have figure 18. 5. CONCLUSION and FUTURE WORK Visual cryptography (VC) is an image-based secret sharing method in which the decoding process is done by inspecting the superimposed shares using naked eye without any computer computation. The shares generated using conventional VC schemes are noise-like to assure the protected secret unreadable, while those created by extended VC schemes are meaningful to further conceal the track of the secret. In this scheme, we can divide a secret image into two or more number of shares. The shares are sent through different communication channels from sender to receiver so that the probability of getting sufficient shares by the intruder minimized. But the shares may arise suspicion to the hacker s mind that some secret information is passed. The original image can be encrypted using a key to provide more security to this scheme. The key may be a text or a small image. Steganography can be used by enveloping the secret shares within apparently innocent covers of digital picture. This technique is more effective in providing security from illicit attacks. Future work will extend the current work for secret communication by studying the tradeoff between the resolution and quality of the embedded secrets. Page 58
REFERENCES [1] Hyoung Joong Kim, Yongsoo Choi, A New Visual Cryptography Using Natural Images, IEEE, 2005. [2] Yuan Tai Hsu Long Wen Chang, A New Construction Algorithm of Visual Crytography for Gray Level Images, IEEE, 2006. [3] Arun Ross, Senior Member, IEEE, and Asem Othman, Visual Cryptography for Biometric Privacy, IEEE transactions on information forensics and security, vol. 6, no. 1, March 2011. [4] Nazanin Askari, Cecilia Moloney, H. M. Heys, A Novel Visual Secret Sharing Scheme without Image Size Expansion, IEEE, 2012. [5] Ching-Nung Yang, Senior Member, IEEE, and Dao- Shun Wang, Property Analysis of XOR-Based Visual Cryptography, IEEE transactions on circuits and systems for video technology, vol. 24, no. 2, February 2014. [6] Young-Chang Hou, Shih-Chieh Wei, and Chia-Yin Lin, Random-grid-based Visual Cryptography Schemes, IEEE, 2013. [7] Dao-Shun Wang, Member, IEEE, Tao Song, Lin Dong, and Ching-Nung Yang, Optimal Contrast Grayscale Visual Cryptography Schemes With Reversing, IEEE transactions on information forensics and security, vol. 8, no. 12, December 2013. [8] Kai-Hui Lee and Pei-Ling Chiu, Digital Image Sharing by Diverse Image Media,IEEE transactions on information forensics and security, vol. 9, no. 1, January 2014. Page 59