Improved Visual Secret Sharing Scheme for QR Code Applications

Cheng, Yuqiao; Fu, Zhengxin; Yu, Bin

doi:10.1109/tifs.2018.2819125

Cited by 71 publications

(30 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, this paper presents a novel NMF framework to factorize a Chinese character represented as a binary image (or matrix). Furthermore, we evaluate the performance of the proposed NMF technique by applying it to the application of visual secret sharing (a visual cryptographic technique [31][32][33][34][35] in information security [36][37][38]) that securely shares secret messages encoded as binary images of partial Chinese characters.…”

Section: Main Objective Of This Papermentioning

confidence: 99%

A novel non-negative matrix factorization technique for decomposition of Chinese characters with application to secret sharing

Lin

Huang

et al. 2019

EURASIP J. Adv. Signal Process.

View full text Add to dashboard Cite

The decomposition of Chinese characters is difficult and has been rarely investigated in the literature. In this paper, we propose a novel non-negative matrix factorization (NMF) technique to decompose a Chinese character into several graphical components without considering the strokes of the character or any semantic or phonetic properties of the components. Chinese characters can usually be represented as binary images. However, traditional NMF is only suitable for representing general gray-level or color images. To decompose a binary image using NMF, we force all of the elements of the two matrices (obtained by factorizing the binary image/matrix to be decomposed) as close to 0 or 1 as possible. As a result, a Chinese character can be efficiently decomposed into several components, where each component is semantically unreadable. Moreover, our NMF-based Chinese character decomposition method is suitable for applications in visual secret sharing by distributing the shares (different character components) among multiple parties, so that only when the parties are taken together with their respective shares can the secret (the original Chinese character(s)) be reconstructed. Experimental results have verified the decomposition performance and the feasibility of the proposed method.

show abstract

Section: Main Objective Of This Papermentioning

confidence: 99%

A novel non-negative matrix factorization technique for decomposition of Chinese characters with application to secret sharing

Lin

Huang

et al. 2019

EURASIP J. Adv. Signal Process.

View full text Add to dashboard Cite

show abstract

“…Note that the ( , , ) values are different for certain level of error correction in some QR code versions. It can be found that there are 5 error correction blocks in version 7 with an level of error correction of H. The ( , , ) values for the first four blocks are (39, 13,13) where the value for the last one is (40, 14,13).…”

Section: Qr Codesmentioning

confidence: 99%

“…Wan et al [10] proposed a scheme that deeply integrated the QR code error correction mechanism with the theory of VSS and the region shared with the secret image is continuous. Chen et al [14] proposed a VSS scheme with high security and flexible access structures for QR code applications. Chow et al [15] investigated a method to distribute shares through embedding them into QR codes cover by a secure way using cryptographic keys.…”

Section: Introductionmentioning

confidence: 99%

“…end for(14) Output grayscale shares 1 , 2 , ⋅ ⋅ ⋅ , .Algorithm 1: Proposed robust VSS applying to QR codes.Input: shares 1 , 2 , ⋅ ⋅ ⋅ ,; threshold parameters ( , )( ≥ 2); Output: the reconstructed secret QR code image . (1) for = 1 to do (Read the secondary plane of share to create binary QR image as (3) end for (Read the version as v and level of error correction noted as l of image 1 with QR code decoder.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Robust Visual Secret Sharing Scheme Applying to QR Code

Tan

Liu

Yan

et al. 2018

Security and Communication Networks

View full text Add to dashboard Cite

Different color patterns of quick response (QR) codes, such as RGB, grayscale, and binary QR codes, are widely used in applications. In this paper, we propose a novel XOR-based visual secret sharing (VSS) scheme using grayscale QR codes as cover images and binary QR code as secret image. First, all the codewords of the secret QR code image are encoded into n temporary binary QR code images, which are substituted for the second significant bit planes of the grayscale QR code cover images to generate n shares. Each share is a grayscale QR code image, which can be decoded by a standard QR code decoder, so that it may not attract the attention of potential attackers when distributed in the public channel. The secret image can be recovered by XORing the codewords regions of QR codes which are extracted from the second significant bit planes of the grayscale shares. More importantly, the proposed scheme is robust to JPEG compression, addition of different noises, rotation, resizing, and cropping, which is useful in practice. The effectiveness and robustness of our scheme are shown by the experimental results. The application of QR code is suitable for wireless multimedia data security.

show abstract

“…Wan et al [13] continuously embedded a secret image into QR codes by integrating the theory of VSS and the error correction mechanism of QR codes. Chen et al [1] presented a scheme using QR codes for applications involving security and flexible access structures. Chow et al [2] used cryptographic keys to encrypt QR codes when embedding them into cover QR codes.…”

Section: Introductionmentioning

confidence: 99%

XOR-ed visual secret sharing scheme with robust and meaningful shadows based on QR codes

Tan

Yan

et al. 2019

Multimed Tools Appl

View full text Add to dashboard Cite

Quick response (QR) codes are becoming increasingly popular in various areas of life due to the advantages of the error correction capacity, the ability to be scanned quickly and the capacity to contain meaningful content. The distribution of dark and light modules of a QR code looks random, but the content of a code can be decoded by a standard QR reader. Thus, a QR code is often used in combination with visual secret sharing (VSS) to generate meaningful shadows. There may be some losses in the process of distribution and preservation of the shadows. To recover secret images with high quality, it is necessary to consider the scheme's robustness. However, few studies examine robustness of VSS combined with QR codes. In this paper, we propose a robust (k, n)-threshold XOR-ed VSS (XVSS) scheme based on a QR code with the error correction ability. Compared with OR-ed VSS (OVSS), XVSS can recover the secret image losslessly, and the amount of computation needed is low. Since the standard QR encoder does not check if the padding codewords are correct during the encoding phase, we replace padding codewords by initial shadows shared from the secret image using XVSS to generate QR code shadows. As a result, the shadows can be decoded normally, and their error correction abilities are preserved. Once all the shadows have been collected, the secret image can be recovered losslessly. More importantly, if some conventional image attacks, including rotation, JPEG compression, Gaussian noise, salt-and-pepper noise, cropping, resizing, and even the addition of camera and screen noises are performed on the shadows, the secret image can still be recovered. The experimental results and comparisons demonstrate the effectiveness of our scheme.

show abstract

Improved Visual Secret Sharing Scheme for QR Code Applications

Cited by 71 publications

References 19 publications

A novel non-negative matrix factorization technique for decomposition of Chinese characters with application to secret sharing

A novel non-negative matrix factorization technique for decomposition of Chinese characters with application to secret sharing

Robust Visual Secret Sharing Scheme Applying to QR Code

XOR-ed visual secret sharing scheme with robust and meaningful shadows based on QR codes

Contact Info

Product

Resources

About