A novel secret image sharing scheme in color images using small shadow images

Over the past several years, secret image sharing techniques have become another branch of the effort to prevent secret images from being eavesdropped on, in addition to traditional cryptography. Because smaller shadows can speed up the transmission of a secret color image, in this paper we combine Chang and Wu’s gradual search algorithm for a single bitmap BTC (GSBTC) and Shamir’s (k, n) threshold concept to propose a novel secret color image sharing scheme that generates smaller shadows. Experimental results confirm that the proposed scheme successfully reduces shadow size and that each shadow behaves as a random-like image that prevents leakage of information about the secret color image. Furthermore, the correlation between two vertically or horizontally adjacent pixels in each shadow is significantly less than those in a color secret image, and the presented scheme also achieves, on average, an NPCR = 0.414% and AUCI = 32.78%. Thus, with our scheme one-pixel difference could cause a significant difference in the corresponding shadows. Therefore, the security of the presented scheme is also confirmed.     

A hierarchical threshold secret image sharing

In the traditional secret image sharing schemes, the shadow images are generated by embedding the secret data into the cover image such that a sufficient number of shadow images can cooperate to reconstruct the secret image. In the process of reconstruction, each shadow image plays an equivalent role. However, a general threshold access structure could have other useful properties for the application. In this paper, we consider the problem of secret shadow images with a hierarchical threshold structure, employing Tassa’s hierarchical secret sharing to propose a hierarchical threshold secret image sharing scheme. In our scheme, the shadow images are partitioned into several levels, and the threshold access structure is determined by a sequence of threshold requirements. If and only if the shadow images involved satisfy the threshold requirements, the secret image can be reconstructed without distortion.     

A general (k, n) scalable secret image sharing scheme with the smooth scalability

A novel (k, n) scalable secret image sharing (SSIS) scheme was proposed to encrypt a secret image into n shadow images. One can gradually reconstruct a secret image by stacking k or more shadows, but he/she cannot conjecture any information from fewer than k shadows. The advantage of a (k, n)-SSIS scheme is that it provides the threshold property (i.e., k is a threshold value necessary to start in to reveal the secret) as well as the scalability (i.e., the information amount of a reconstructed secret is proportional to the number of shadows used in decryption). All previous (k, n)-SSIS schemes did not have the smooth scalability so that the information amount can be “smoothly” proportional to the number of shadows. In this paper, we consider the smooth scalability in (k, n)-SSIS scheme.     

Reversible secret-image sharing with high visual quality

This paper proposes a reversible secret-image sharing scheme for sharing a secret image among 2n shadow images with high visual quality (i.e., they are visually indistinguishable from their original images, respectively). In the proposed scheme, not only can the secret image be completely revealed, but the original cover images can also be losslessly recovered. A difference value between neighboring pixels in a secret image is shared by 2n pixels in 2n shadow images, respectively, where n?≥?1. A pair of shadow images which are constructed from the same cover image are called brother stego-images. To decrease pixel values changed in shadow images, each pair of brother stego-images is assigned a weighted factor when calculating difference values to be shared. A pixel in a cover image is recovered by calculating the average of corresponding pixels in its brother stego-images. A single stego-image reveals nothing and a pair of pixels in brother stego-images reveals partial difference value between neighboring secret pixels. The more brother stego-images are collected, the more information in the secret image will be revealed. Finally, a secret image will be completely revealed if all of its brother stego-images are collected.     

基于CRT的无损高效门限彩色图像秘密共享信息隐藏算法

目前对秘密图像共享的研究主要集中在灰度图像上,而日常生活中使用的图像大多是彩色的,因此,研究彩色图像的秘密共享具有重要的意义和应用价值.该方案将基于中国剩余定理(CRT)的秘密共享与DCT信息隐藏技术进行结合,保障了传输彩色秘密图像的安全性.在生成端,利用DCT信息隐藏算法将彩色秘密图像通过CRT生成的彩色秘密影子图像...     

基于区域卷积神经网络的图像秘密共享方案

数字图像在如今网络高速发展时代已成为重要的信息载体,而对图像信息的安全保护也成为安全领域的重要研究课题.图像秘密共享方案是一种基于门限的密码学方案,能够为多个用户提供一种保护图像秘密信息的方案.该方案将秘密图像加密成若干个影子图像,分配给不同的用户.当用户的个数达到门限值后,原始图像可以被重构,否则用户无法获得原始图像的任何信息.图像信息的分类和识别是图像秘密共享的前提和基础,卷积神经网络(convolutional neural network, CNN)在图像分类和识别中具有较高的准确性和较快的速度.将基于卷积神经网络的图像识别和分类与图像秘密共享结合起来,将深度学习工具应用于图像信息保护,可以提高基于传统人工图像识别的图像保护方案的效率.首先采用区域卷积神经网络(region CNN, RCNN)模型对图像进行识别,根据所包含的信息内容将图像分割成重要性级别不同的若干区域,然后在此基础上构造2种图像秘密共享方案,渐进式重构图像秘密共享方案以及具有重要影子图像的图像秘密共享方案.其中重要性级别较高的图像区域在图像重构中需要较高的门限,这一特性使得图像秘密共享方案能够适用于更多的应用场景.与传统的基于人工特征的图像识别方法相比,神经网络的引用能够提升图像分类和识别的效率,从而进一步提升了图像秘密共享的应用价值.     

Greyscale-images-oriented progressive secret sharing based on the linear congruence equation

Secret image sharing (SIS) can be applied to protect a secret image when the secret is transmitted in public channels. However, classic SIS schemes, e.g., visual secret sharing (VSS) and Shamir’s polynomial-based scheme, are not suitable for progressive encryption of greyscale images, because they will lead to many problems, such as “All-or-Nothing”, lossy recovery, complex computations and so on. Based on the linear congruence equation, three novel progressive secret sharing (PSS) schemes are proposed to overcome these problems: (k, k) threshold LCSS and (k, n) threshold LCPSS aim to achieve general threshold progressive secret sharing with simple computations. Furthermore, extended LCPSS (ELCPSS) is developed to generate meaningful shadow images, which enable simple management and misleading the enemy. Both theoretical proofs and experimental results are given to demonstrate the validity of the proposed scheme.     

Reduce shadow size in aspect ratio invariant visual secret sharing schemes using a square block-wise operation

An aspect ratio invariant visual secret sharing (ARIVSS) scheme is a perfectly secure method for sharing secret images. Due to the nature of the VSS encryption, each secret pixel is expanded to m sub-pixels in each of the generated shares. The advantage of ARIVSS is that the aspect ratio of the recovered secret image is fixed and thus there is no loss of information when the shape of the secret image is our information. For example, a secret image of a circle is compromised to an ellipse if m does not have a square value. Two ARIVSS schemes based on processing one and four pixel blocks, respectively, were previously proposed. In this paper, we have generalized the square block-wise approach to further reduce pixel expansion.     

A novel (n,t, n) secret image sharing scheme without a trusted third party

Secret image sharing is a technique to share a secret image among a set of n participants. A trusted third party embeds the secret image into the cover image to generate shadow images such that at least t or more shadow images can reconstruct the secret image. In this paper, we consider an extreme and real-world situation, in which there is no one who is trusted by anyone else. In the proposed scheme, the participants can act as a dealer and communicate with each other in a secret channel. Each participant can generate her/his own shadow image independently, according to the cover image and the secret image. Experimental results are provided to show that the shadow images have satisfactory quality. In addition, our scheme has a large embedding capacity, and the secret image can be reconstructed losslessly.     

Sharing and hiding secret images with size constraint

This paper presents a method for sharing and hiding secret images. The method is modified from the (t,n) threshold scheme. (Comput.Graph. 26(5)(2002)765) The given secret image is shared and n shadow images are thus generated. Each shadow image is hidden in an ordinary image so as not to attract an attacker's attention. Any t of the n hidden shadows can be used to recover the secret image. The size of each stego image (in which a shadow image is hidden) is about 1/t of that of the secret image, avoiding the need for much storage space and transmission time (in the sense that the total size of t stego images is about the size of the secret image). Experimental results indicate that the qualities of both the recovered secret image and the stego images that contain the hidden shadows are acceptable. The photographers who work in enemy areas can use this system to transmit photographs.     

视图的秘密分享及其代数编码方法

视图的秘密分享是图像信息安全领域独具吸引力的研究问题。寻求秘密视图完全的(Perfect)和理想的(Ideal)门限秘密分享方案(也称图像门限分享的完备方案),则是其中富有挑战性的未决课题。文中引入灰度值域GF(2m)上像素矩阵秘密分享的新观点和相应的代数几何编码方法,实现了数字图像(t,n)门限秘密分享的一种完备方案。该方案能够将一幅或多幅秘密图像编码为n幅各具随机视觉内容,同时又共具(t,n)门限结构的影子图像(或称份额图像)。证明了这种秘密分享方案的(t,n)门限结构不仅是完全的而且也是理想的,并给出了提高像素灰度值域GF(2m)上图像秘密分享算法效率的“m位像素值的分拆与并行”方法。分析表明,该图像秘密分享方法可以应用于高安全等级的秘密图像的网络多路径传输、保密图像信息的分散式存储控制、高维图形码(Bar-code in k dimension)和弹出码(Popcode)等新一代信息载体技术的识读控制等各方面。     

Medical image security and EPR hiding using Shamir's secret sharing scheme

Medical applications such as telediagnosis require information exchange over insecure networks. Therefore, protection of the integrity and confidentiality of the medical images is an important issue. Another issue is to store electronic patient record (EPR) in the medical image by steganographic or watermarking techniques. Studies reported in the literature deal with some of these issues but not all of them are satisfied in a single method. A medical image is distributed among a number of clinicians in telediagnosis and each one of them has all the information about the patient's medical condition. However, disclosing all the information about an important patient's medical condition to each of the clinicians is a security issue. This paper proposes a (k, n) secret sharing scheme which shares medical images among a health team of n clinicians such that at least k of them must gather to reveal the medical image to diagnose. Shamir's secret sharing scheme is used to address all of these security issues in one method. The proposed method can store longer EPR strings along with better authenticity and confidentiality properties while satisfying all the requirements as shown in the results.     

Two secret sharing schemes based on Boolean operations

Traditional secret sharing schemes involve complex computation. A visual secret sharing (VSS) scheme decodes the secret without computation, but each shadow is m times as big as the original. Probabilistic VSS solved the computation complexity and space complexity problems at once. In this paper we propose a probabilistic (2,n) scheme for binary images and a deterministic (n,n) scheme for grayscale images. Both use simple Boolean operations and both have no pixel expansion. The (2,n) scheme provides a better contrast and significantly smaller recognized areas than other methods. The (n,n) scheme gives an exact reconstruction.     

高效免置乱的图像秘密共享方案

针对图像秘密共享前需要像素置乱的问题,基于(t, n)门限多重秘密共享思想,提出一种免置乱的图像秘密共享方案,以第n+1人的秘密份额作为因子参与秘密分割与重构,加大相邻像素之间的差距。该方案无需进行额外的密钥传输,运算简单高效、易于扩展,生成的影子图像也仅为原图像的1/t,有效压缩了尺寸。实验结果证明了该方案的可行性。     

一种可压缩的(r,n)门限秘密图像共享方案

提出了一种可压缩的(r,n)门限秘密图像共享方案,Shamir的门限方案是该方案的基础,它可以克服VSS方案的缺点,并能把影子图像压缩成原秘密图像大小的1/r;当所有像素灰度值小于250时,恢复图像和原秘密图像一样。随后对该方案进行改进,使其在有像素灰度值大于250的情况下,可获得无质量损失的恢复图像。     

基于恢复函数和误差扩散的灰度图像分存方案

基于((n,n)-阈值的灰度图像分存方案利用恢复函数和误差扩散技术将一张秘密灰度图像分存到n张有意义的灰度分存图像中。所提方案选择n张有意义的灰度图像作为分存图像,以增强秘密图像的隐蔽性,达到保护图像信息安全的目的;采用误差扩散技术,可以产生具有良好视觉质量的分存图像。所生成的分存图像没有像素膨胀,其大小与秘密图像相等。此外,方案的重构过程简单快速,而且是无损的。实验结果和理论分析表明,所提方案能为秘密图像分存提供一个高安全和有效的机制。     

基于ID的门限多重秘密共享方案

为了避免现有秘密共享方案中的秘密份额分发机制的不足,结合基于身份(ID)的公钥密码技术,提出了利用参与者私钥作为其主份额的秘密份额分发方法.首先,对Zheng提出的签密方案进行了安全分析,发现其不具备前向保密性,并针对该安全问题,提出了一个改进的签密方案.同时,在所提出的改进方案的基础上,结合基于ID的公钥密码系统,提出了一个新的门限多重秘密共享方案.该方案有效地解决了秘密份额的安全分发问题,不需要秘密分发者和参与者之间事先进行任何信息交互,能够在分发秘密的同时分发秘密份额.该方案还具有前向保密性,即使秘密分发者的私钥被泄漏,也不会影响之前所共享秘密的安全性.因此,所提出的基于身份的秘密共享方案具有更高的安全性和有效性,能够更好地满足应用需求.     

基于ElGamal密码体制的可验证秘密共享方案

基于ElGamal密码体制,提出了一个新的可验证秘密共享方案.方案中,秘密份额由各个参与者自己选择,秘密分发者不知道各个参与者所持有的份额,而且秘密份额长度与共享秘密长度相同.重构秘密时,任一参与者只需计算一次即可确认参与者中是否存在欺诈者,欺诈成功的概率可忽略不计.若存在欺诈者,则可通过秘密分发者来确定欺诈者身份.该方案具有充分的秘密信息利用率和较少的验证计算量.当共享秘密更换时,参与者不必更换自己的秘密份额.并且,每个参与者只需维护一个秘密份额,就可以实现对多个秘密的共享.方案的安全性是基于ElGamal密码体制和Shamir门限方案的安全性.     

Probabilistic visual secret sharing schemes for grey-scale images and color images

Visual secret sharing (VSS) scheme is an encryption technique that utilizes the human visual system in recovering the secret image and does not require any cryptographic computation. Pixel expansion has been a major issue of VSS schemes. A number of probabilistic VSS schemes with minimum pixel expansion have been proposed for binary secret images. This paper presents a general probabilistic (k, n)-VSS scheme for grey-scale images and another scheme for color images. With our schemes, the pixel expansion can be set to a user-defined value. When this value is 1, there is no pixel expansion at all. The quality of reconstructed secret images, measured by average contrast (or average relative difference), is equivalent to the contrast of existing deterministic VSS schemes. Previous probabilistic VSS schemes for black-and-white images can be viewed as special cases in the schemes proposed here.     

A high quality and small shadow size visual secret sharing scheme based on hybrid strategy for grayscale images

Many secret sharing schemes for digital images have been developed in recent decades. Traditional schemes typically must deal with the problem of computational complexity, and other visual secret sharing schemes come with a higher transmission cost and storage cost; that is, each shadow size is m times as big as the original secret image. The new (2,n) secret sharing scheme for grayscale images proposed in this paper is based a combination of acceptable image quality using block truncation coding (BTC), high compression ratio discrete wavelet transform (DWT) and good subjective performance of the vector quantization (VQ) technique. Experimental results confirm that our proposed scheme not only generates a high quality reconstructed original image but also generates small, random-like grayscale shadows.