A blind watermarking algorithm based on fractional Fourier transform and visual cryptography

This paper presents a robust copyright protection scheme based on fractional Fourier transform (FrFT) and visual cryptography (VC). Unlike the traditional schemes, in our scheme, the original image is not modified by embedding the watermark into the original image. We use the visual secret sharing scheme to construct two shares, namely, master share and ownership share. Features of the original image are extracted using SVD, and are used to generate the master share. Ownership share is generated with the help of secret image (watermark) and the master share, using VC technique. The two shares separately give no information about the secret image, but for ownership identification, the secret image can be revealed by stacking the master share and the ownership share. In order to achieve the robustness and security, the properties of VC, FrFT and SVD are used in our scheme. The experimental results show that the proposed scheme is strong enough to resist various signal processing operations.     

信息安全和密码技术分析

我国信息安全防护起步晚、基础差,而且网络安全防护能力也比较低,计算机的核心技术在美国,安全设备还要靠国外引进,缺乏安全保障,无法保障国家信息的安全。因此必须要对信息安全及密码技术有全面认识及应用。本文则对信息安全及密码技术探讨。     

Improving the visual quality of size invariant visual cryptography scheme

In order to reduce the pixel expansion of visual cryptography scheme (VCS), many size invariant visual cryptography schemes (SIVCS’s) were proposed. However, most of the known SIVCS’s have bad visual quality and thin line problems, hence the known SIVCS’s are only suitable to encrypt coarse secret images. In this paper, we notice that the variance of the darkness levels of the pixels also reflects the visual quality of the recovered secret image, as well as the average contrast. We verify, analytically and experimentally, the effectiveness of the variance to be a criterion for evaluating the visual quality of the recovered secret image. Furthermore, we propose two multi-pixel encryption size invariant visual cryptography schemes (ME-SIVCS’s) which improve the visual quality of the recovered secret image by reducing the variance of the darkness levels. In addition, the proposed ME-SIVCS’s can be used to encrypt fine secret images since they avoid some known thin line problems. Experimental results and comparisons are also given to show the effectiveness of the proposed ME-SIVCS’s. Finally, we give suggestions on obtaining good visual quality for the recovered secret image.     

Multi-factor cheating prevention in visual secret sharing by hybrid codebooks

Visual secret sharing, or the so-called visual cryptography, is a well-known scheme that encrypts a secret image into several meaningless share images, usually printed on transparencies, and decrypts as stacking some or all share images by the human visual system. More and more researches about visual secret sharing and its applications have been recently proposed. Unfortunately, the cheating attack in which malicious participants cheat the honest one(s) by forging a fake share image has existed. Since 2006, some cheating prevention schemes have been proposed but suffered from one or more disadvantages as follows: (1) maintaining extra share images used to verify the integrity of a share image prior to stacking, (2) introducing extra pixel expansion, (3) raising heavy computation cost, and (4) giving ambiguous cheating detection. In this paper, a multi-factor cheating–preventing scheme, aiming at exploiting the hybrid codebook to hide the additional verification images into the share images, has been proposed without suffering the above-mentioned deficiencies. Two-factor cheating–detection exploits the design of verification to both share images and stacked results to deter attackers’ cheating. The experimental results demonstrate the proposed scheme is feasible.     

(t,k, n) XOR-based visual cryptography scheme with essential shadows

Visual cryptography scheme (VCS) shares a binary secret image into multiple shadows, only qualified set of shadows can reveal the secret image by stacking operation. However, VCS suffers the problems of low visual quality of the revealed image and large shadow size. A (t, k, n) XOR-based visual cryptography scheme (XVCS) shares the secret image into n shadows including t essentials and n-t non-essentials. A qualified set of shadows contains any k shadows including t essentials. The revealing process is implemented by XOR operation on the involved shadows. In this paper, we propose a construction method for (t, k, n)-XVCS with essential shadows. The secret image can be revealed perfectly, and the shadow size is small compared with VCS. Theoretical analysis and experimental results show the security and effectiveness of the proposed scheme.     

HP-VCS: A high-quality and printer-friendly visual cryptography scheme

Visual Cryptography Scheme (VCS) is a secret-sharing scheme which aims to encrypt a secret message into multiple shares and transmit them to participants over an untrusted communication channel. Although human vision can easily reveal the secret message by stacking a sufficient number of shares, this scheme reduces the visual quality of recovered images. This paper presents a novel high-quality and printer-friendly VCS. When providing high-quality recovery, this scheme keeps the size of the shares the same as the secret image. Experimental results show that, compared with previous work, the proposed scheme significantly improves the performance of recovered images.     

Multi-layer fusion network for blind stereoscopic 3D visual quality prediction

Stereoscopic 3D (S3D) visual quality prediction (VQP) is used to predict human perception of visual quality for S3D images accurately and automatically. Unlike that of 2D VQP, the quality prediction of S3D images is more difficult owing to complex binocular vision mechanisms. In this study, inspired by the binocular fusion and competition of the binocular visual system (BVS), we designed a blind deep visual quality predictor for S3D images. The proposed predictor is a multi-layer fusion network that fuses different levels of features. The left- and right-view sub-networks use the same structure and parameters. The weights and qualities for the left- and right-view patches of S3D images can be predicted. Furthermore, training patches with more saliency information can improve the accuracy of prediction results, which also make the predictor more robust. The LIVE 3D Phase I and II datasets were used to evaluate the proposed predictor. The results demonstrate that the performance of the proposed predictor surpasses most existing predictors on both asymmetrically and symmetrically distorted S3D images.     

Constructions of general (k,n) reversible AMBTC-based visual cryptography with two decryption options

In this paper, a general method of $(k\text{,}n)$ threshold Reversible Absolute moment block truncation coding Visual Cryptography Scheme (RAVCS) is introduced for sharing a binary secret image into multiple absolute moment block truncation coding (AMBTC) shadows. A $(k\text{,}k)$ RAVCS is firstly proposed to encode a secret by referencing one ABMTC image. Then, the proposed $(k\text{,}k)$ RAVCS is adopted to share the same secret into multiple groups of shadows by referencing multiple images. Those multiple groups of shadows are distributed to participants according to a matrix generated by the proposed shadow distribution algorithms. When any k or more participants share their shadows, the secret image is revealed by OR or XOR decryption. Further, those AMBTC shadows can be losslessly reverted to their original forms. Sufficient theoretical analysis and extensive experimental results are provided in this paper, showing the effectiveness and advantages of the proposed method.     

Sharing more information in gray visual cryptography scheme

Visual cryptography scheme (VCS) shares a binary secret image into several binary shadows, and the secret image can be visually revealed by stacking qualified shadows without computation. From the point of view of sharing secret information, VCS is not efficiency because of the large size expansion and low visual quality. In this paper, we introduce a general gray visual cryptography scheme, which can share more information, called Sharing More Information Gray Visual Cryptography Scheme (SMIGVCS). All the shadow pixels of VCS embed additional information to generate gray shadows of SMIGVCS, and the embedded information comes from the shadows of a polynomial-based secret sharing scheme (PSSS). In the revealing process, a vague secret image is visually decoded by stacking qualified shadows, and more information is revealed by computation. Compared with the two-in-one image secret sharing scheme (TiOISSS), our SMIGVCS can achieve smaller shadow size with acceptable visual quality.     

基于机器视觉的车辆上磅位置作弊检测系统设计

针对目前汽车衡计量中存在的车辆上磅位置作弊现象,提出一种基于机器视觉的车辆上磅作弊检测系统.首先分析了该系统组成及原理,然后设计了车辆上磅位置作弊检测算法,并利用GSM网络短消息业务功能实现在线远程报警.该系统能有效降低企业建设成本,减少称重系统舞弊现象,具有较好实用价值和应用前景.     

视觉零知识身份认证的研究

零知识证明协议是一种非常强大的密码系统。大部分的零知识身份识别方案的安全性是基于复杂的数学算法,和交互双方大规模的计算,即证明者和示证者。而视觉密码技术是一种特别的不需要了解密码学和相应的复杂的数学计算的密码学。因此提出了一个新的基于视觉密码的零知识身份证明方法,克服了当前零知识身份证明协议依赖计算设备和复杂计算。     

GF(2m)椭圆曲线密码体制在智能卡中的应用

介绍了特征2域上的椭圆曲线密码体制（ECC）的理论基础。分析了智能卡的安全机制，将椭圆曲线密码体制应用到智能卡中，给出了椭圆曲线密码算法在智能卡数据加密中的实现，并给出了在智能卡pin验证中的应用流程。最后，对ECC智能卡的性能进行了分析。     

电子商务中的主要信息加密技术分析及其应用

论述和分析了加密技术及其在电子商务安全方面的应用。在对称加密体制方面,重点讨论了DES算法,给出了其在密钥管理、安全应用方面存在的问题;在非对称加密体制方面重点研究RSA及其应用中存在的问题。     

Advanced modeling of visual information processing: A multi-resolution directional-oriented image transform based on Gaussian derivatives

In this work, a multi-channel model for image representation is derived based on the scale-space theory. This model is inspired in biological insights and includes some important properties of human vision such as the Gaussian derivative model for early vision proposed by Young [The Gaussian derivative theory of spatial vision: analysis of cortical cell receptive field line-weighting profiles, General Motors Res. Labs. Rep. 4920, 1986]. The image transform that we propose in this work uses analysis operators similar to those of the Hermite transform at multiple scales, but the synthesis scheme of our approach integrates the responses of all channels at different scales. The advantages of this scheme are: (1) Both analysis and synthesis operators are Gaussian derivatives. This allows for simplicity during implementation. (2) The operator functions possess better space-frequency localization, and it is possible to separate adjacent scales one octave apart, according to Wilson's results on human vision channels. [H.R. Wilson, J.R. Bergen, A four mechanism model for spatial vision. Vision Res. 19 (1979) 19–32). (3) In the case of two-dimensional (2-D) signals, it is easy to analyze local orientations at different scales. A discrete approximation is also derived from an asymptotic relation between the Gaussian derivatives and the discrete binomial filters. We show in this work how the proposed transform can be applied to the problems of image coding, noise reduction and image fusion. Practical considerations are also of concern.     

Feature compression: A framework for multi-view multi-person tracking in visual sensor networks

Visual sensor networks (VSNs) consist of image sensors, embedded processors and wireless transceivers which are powered by batteries. Since the energy and bandwidth resources are limited, setting up a tracking system in VSNs is a challenging problem. In this paper, we present a framework for human tracking in VSNs. The traditional approach of sending compressed images to a central node has certain disadvantages such as decreasing the performance of further processing (i.e., tracking) because of low quality images. Instead, we propose a feature compression-based decentralized tracking framework that is better matched with the further inference goal of tracking. In our method, each camera performs feature extraction and obtains likelihood functions. By transforming to an appropriate domain and taking only the significant coefficients, these likelihood functions are compressed and this new representation is sent to the fusion node. As a result, this allows us to reduce the communication in the network without significantly affecting the tracking performance. An appropriate domain is selected by performing a comparison between well-known transforms. We have applied our method for indoor people tracking and demonstrated the superiority of our system over the traditional approach and a decentralized approach that uses Kalman filter.     

3种颜色空间的亮度分量在伪装效果评价中的应用

结合伪装效果评价的要求,以中国颜色体系为基础,建立了CIE1976L*a*b*、LMS、ιαβ这3种颜色空间的64级亮度分量数据库,利用灰度直方图相似度算法,分析了以上3种亮度分量在伪装效果评价中的应用问题.实验结果表明,L*分量具有均匀性较好,Lm分量和ι分量分别在灰度较低和灰度较高时,其伪装效果的评价结果与人眼判读...     

基于Linux环境下的IPS实现算法研究及性能测试

入侵防御系统（IPS）是继入侵检测系统（IDS）之后网络安全领域的一个新的研究方向，它既可以用来检测，又可以用来防御和阻止攻击。文中首先讨论了在Linux操作系统下的入侵防御系统，然后给出了建立入侵防御系统的3种算法，并对其性能做了测试、比较和分析，最后讨论了进一步需要研究的问题。