Multiple-image encryption scheme with a single-pixel detector

Abstract

A multiple-image encryption (MIE) scheme with a single-pixel detector has been proposed according to the principle of ghost imaging. In this scheme, each of the spatially coherent laser beams is modified by a set of phase-mask keys and illuminates on a secret image. All of the transmitted lights are recorded together by a single-pixel (bucket) detector to obtain a ciphertext, but anyone of the secret images can be decrypted from the ciphertext independently without any mutually overlapped despite some noise in them. The MIE scheme will bring convenience for data storage and transmission, especially in the case that different secret images need to be distributed to different authorized users, because the ciphertext is a real-valued function and this scheme can effectively avoid the secret images being extracted mutually. The basic principle of the MIE scheme is described theoretically and verified by computer simulations. Finally, the feasibility, robustness and encryption capacity are also tested numerically.     

简便制备具有三层准晶异质结构的加密复合材料

加密材料是信息安全领域的一个主要研究方向,然而将复杂编码的完全隐藏、传输过程中的稳定性、伪装性和可靠的解码方法相结合来实现理想的信息安全,仍具有挑战性.本文报道了一种创新策略,用于合理构建具有高安全性和便携性的加密复合材料.与普通的胶体光子水印相比,这种加密光学器件由热塑性聚氨酯(TPU)保护层、聚苯乙烯(PS)转换层...     

Novel bilateral-diffusion image encryption algorithm with compound chaos and LFSR

Abstract

In order to solve the problem of short cycle and low precision of one-dimensional (1D) chaotic function, the new compound two-dimensional chaotic function is presented by exploiting two 1D chaotic functions which are switched randomly. A new chaotic sequence generator is designed by the compound chaos and linear feedback shift register (LFSR). The random properties of compound chaotic functions and LFSR are also proved rigorously. The novel bilateral-diffusion image encryption algorithm and permutation algorithm are proposed based on the compound chaotic function and LFSR, which can produce more avalanche effect and larger key space. The entropy analysis, differential analysis, statistical analysis, cipher random analysis and cipher sensitivity analysis are introduced to test the security of new scheme. The results show that the novel image encryption method passes SP 800-22 standard tests and solves the problem of short cycle and low precision of 1D chaotic function.     

Image encryption combining multiple generating sequences controlled fractional DCT with dependent scrambling and diffusion

Based on the fractional discrete cosine transform with multiple generating sequences (MGSFrDCT) and the dependent scrambling and diffusion (DSD), an image encryption algorithm is proposed, in which the multiple-generating sequences greatly enlarge the key space of the encryption system. The real-valued output of MGSFrDCT is beneficial to storage, display and transmission of the cipher-text. During the stage of confusion and diffusion, the locations and values of all MGSFrDCT transformed coefficients change due to DSD, and the initial values and fractional orders of encryption system depend not only on the cipher keys but also on the plain-image due to introduction of a disturbance factor, which allows the encryption system to resist the known-plaintext and chosen-plaintext attacks. Experimental results demonstrate that the proposed encryption algorithm is feasible, effective and secure and able to resist common classical attacks.     

一种新的基于可逆矩阵的具有完整性检验能力的图像加密方案

为了保护图像信息的安全,论文利用组合理论知识,提出一种新的基于可逆整数矩阵的、具有完整性检验能力的图像加密方案。应用该方案将一个灰度图像加密生成一个脆弱的噪声密图,解密过程是加密的简单逆过程。密图的完整性可以凭借人类视觉系统进行检验,不需要任何复杂的计算。当密图遭受恶意篡改时,解密得到一个噪声图,无法得到原始图像的任何信息。论文加密方案的密钥简单,且密钥空间足够大。理论分析和实验结果证明了,该方案为图像加密提供了一种高安全性和有效的机制。     

Reliability‐based topology optimization against geometric imperfections with random threshold model

This paper develops a new reliability‐based topology optimization framework considering spatially varying geometric uncertainties. Geometric imperfections arising from manufacturing errors are modeled with a random threshold model. The projection threshold is represented by a memoryless transformation of a Gaussian random field, which is then discretized by means of the expansion optimal linear estimation. The structural response and their sensitivities are evaluated with the polynomial chaos expansion, and the accuracy of the proposed method is verified by Monte Carlo simulations. The performance measure approach is adopted to tackle the reliability constraints in the reliability‐based topology optimization problem. The optimized designs obtained with the present method are compared with the deterministic solutions and the reliability‐based design considering random variables. Numerical examples demonstrate the efficiency of the proposed method.     

Queueing models with threshold phenomena: With special reference to machine interference problems

Machine interference problems with state-dependent nonlinear repair rates depicting threshold behaviour are described. Stochastic analysis of the temporal evolution of the number of failed machines is possible by the ‘diffusion approximation’ method which can be systematically carried out to the desired degree of approximation. Thus one is able to study the system’s widely differing stochastic behaviour near and away from the threshold point. Finally we point out the utility of this analysis to computer systems modelling.     

Positive direct-mask stereolithography with multiple-layer exposure: layered fabrication with stair step reduction

In this paper, we explain a new stereolithography involving the separate use of liquid photoinitiator and a base resin (photopolymer resin without photoinitiator). First, the base resin is supplied as a layer, and then a mask pattern is drawn onto the surface with photoinitiator by inkjet printing. When the surface is exposed to a UV lamp, only the pattern drawn with the photoinitiator is cured. In this process, the photoinitiator acts as a positive mask. Also, the idea of multiple-layer exposure, which may enable stair step reduction and fabrication time reduction, is introduced. The proposed idea and method are implemented in an experimental stereolithography system and some experiments are conducted using the system. As a result, the effectiveness and feasibility of the idea and method are confirmed.     

Analysis of multi-degree of freedom strongly non-linear mechanical systems with random input: Part II: equivalent linear system with random matrices and power spectral density matrix

We present a method for estimating the (power spectral density) PSD matrix of the stationary response of lightly damped randomly excited multi-degree of fredom mechanical systems with strong non-linear asymmetrical restoring forces. The PSD matrix is defined as the mean value of the PSD matrix response of an equivalent linear system (ELS) whose damping and stiffness matrices depend on non-linear vibration modes of the associated conservative system, the frequencies and modes shapes being amplitude dependent. Based on a generalized van der Pol transformation and using a stochastic averaging principle, as developed in a companion paper, a stationary probability density function for the amplitude process is derived to characterize the ELS fully. Some possible simplifications of the method, such as modal reduction and/or local linearization, are also discussed. The results obtained are in good agreement with those of direct numerical simulations taking two typical examples.     

Cloud manufacturing service composition and optimal selection with sustainability considerations: a multi-objective integer bi-level multi-follower programming approach

The process of service composition and optimal selection (SCOS) is an important issue in cloud manufacturing (CMfg). However, the current studies on CMfg and SCOS have generally focused on optimising the allocation of resources against quality of service (QoS), in terms of e.g. cost, quality, and time. They have seldom taken the perspective of sustainability into discussion, although sustainability is indispensable in the CMfg environment. Addressing this gap, we aim to (1) propose a comprehensive method to assess the sustainability of cloud manufacturing (SoM) in terms of the economic, environmental, and social aspects; (2) establish a multi-objective integer bi-level multi-follower programming (MOIBMFP) model to simultaneously maximise SoM and QoS from the perspectives of both platform operator and multiple service demanders; and (3) design a hybrid particle swarm optimisation algorithm to solve the proposed MOIBMFP model. The experimental results show that the proposed algorithm is more feasible and effective than the typical multi-objective particle swarm optimisation algorithm when solving the proposed model. In other words, the proposed model and algorithm suggest better alternatives to meet the needs of the platform operator and service demanders in the CMfg environment.     

Methodological approaches for histamine quantification using derivatization by chloroethylnitrosourea and ELISA measurement: Part I. Optimization of derivated histamine detection with coated-plates using optimal design

Using derivatization by chloroethylnitrosourea (CENU) a new strategy was used for raising antibodies directed against hapten (< 300 Da) and the quantification of these haptens by ELISA. After raising antibodies directed against histamine, they were characterized and used for ELISA measurements. The development of a quantitative method needs an optimization of both detection and derivatization step. Experimental design methodology has been applied to optimize the conditions of the detection of the derivatized histamine. Methods and results were closely related.     

A sequential weighted Laplacian‐regularized optimal design for response surface modeling of expensive functions with outliers: An application in linear elastic fracture mechanics

There are several sequential and adaptive strategies designed to reduce the number of experiments in response surface methodology (RSM). However, most of the existing sequential and adaptive methods are sensitive to the existence of possible outliers. In this paper, we propose an active learning methodology based on the fundamental idea of adding a Laplacian penalty to the D‐optimal design and integrate that with robust regression to look for the most informative settings to be measured, while reducing the influence of possible outliers. To leverage the intrinsic geometry of the factor settings in highly nonlinear spaces, we extend the proposed methodology to reproducing Kernel Hilbert space (RKHS). Through an extensive simulation study accompanied by a thorough sensitivity analysis, we show that the proposed framework outperforms traditional RSM designs in the presence of outliers. We also conduct a study utilizing a hierarchical function used in linear elastic fracture mechanics to illustrate practicality of the proposed methodology.     

How to build a robust model against perturbation factors with only a few reference values: A chemometric challenge at ‘Chimiométrie 2007’

Following up on the success of previous chemometric challenges arranged during the annual congress organised by the French Chemometrics Society, the organisation committee decided to repeat the idea for the Chimiometrie 2007 event (http://www.chimiometrie.org/) held in Lyon, France (29-30 November) by featuring another dataset on its website. As for the first contest in 2004, this dataset was selected to test the ability of participants to apply regression methods to NIR data. The aim of Challenge 2007 was to perform a calibration model as robust and precise as possible using a data set with only a few reference values available and submitted to different perturbation factors. The committee received nine answers; this paper summarizes the best three approaches, as well as the approach proposed by the organisers.