基于四维混沌系统生成二值序列的方法及其加密应用

利用四维混沌系统生成混沌序列,给出一种二值序列的生成方法,然后对其性能进行了分析,并和其他方法进行了比较。实验表明这种方法生成的二值序列具有很好的伪随机性以及相关性。把这种方法产生的二值序列用在图像加密中,得到了较好的结果。     

Design and analysis of two stream ciphers based on chaotic coupling and multiplexing techniques

In this paper, we design and implement two new stream ciphers based on Pseudo Chaotic Number Generators (PCNGs) which integrate discrete chaotic maps, namely, Piecewise Linear Chaotic Map (PWLCM), Skewtent and Logistic map. They are weakly coupled by a predefined matrix A for the first PCNG and they are coupled by a binary diffusion matrix D for the second one. Each PCNG includes a chaotic multiplexing technique that allows the enhancement of the robustness of the system. The structure is implemented with finite precision N = 32 bits in C language. Security performance of the proposed stream ciphers is analysed and several cryptanalytic and statistical tests are applied. Experimental results highlight robustness as well as efficiency in terms of computation time of these two stream ciphers.     

基于耦合映像格子模型的时空混沌二值序列及其性能分析

基于耦合映像格子模型。给出了一种时空混沌二值序列的产生方法,并对其性能进行了详细分析。结果表明,该种时空混沌二值序列具有十分理想的随机性和相关性。此外,混沌序列容易产生和控制,具有线性复杂度高、对参数敏感等特性,因此特别适合于在保密通信和密码学等诸多领域中应用。     

A chaotic color image encryption using integrated bit-level permutation

In this paper, a color image encryption algorithm based on chaos has been proposed. We convert the color image into three bit-level images (R, G, B components) and combine them to one bit-level image. Then, only use bit-level permutation architecture based on chaotic system to encrypt the integrated image. When diffuse the position of the integrated binary image, the value of the gray pixel is changed as well, so this architecture can achieve similar security to permutation-diffusion architecture. Besides, this architecture makes the three color components affect each other, it can reduce the correlations between three components. Simulation results show that the algorithm can encrypt the color image effectively and resist various typical attacks.     

Security problems for a pseudorandom sequence generator based on the Chen chaotic system

Recently, a novel pseudorandom number generator scheme based on the Chen chaotic system was proposed. In this study, we analyze the security weaknesses of the proposed generator. By applying a brute force attack on a reduced key space, we show that 66% of the generated pseudorandom number sequences can be revealed. Executable C# code is given for the proposed attack. The computational complexity of this attack is O(n), where n is the sequence length. Both mathematical proofs and experimental results are presented to support the proposed attack.     

切延迟椭圆反射腔映射系统混沌序列的改进与彩色图像加密算法

为了提高切延迟椭圆反射腔映射系统(TD-ERCS)的性能,实现对彩色图像信息的有效保护,提出了一种对TD-ERCS混沌序列的改进和基于该改进序列的彩色图像加密算法。分析与研究了TD-ERCS并加以改进,得到随机性能理想的四维混沌实值序列和二值序列;将彩色图像RGB三分量合成一图像后应用改进的TD-ERCS混沌序列以8×8分块置乱,从而加密图像。理论分析和实验结果表明,TD-ERCS改进序列性能更好;彩色图像加密算法密钥空间大,具有较好的加密效果和高的加密效率,并对统计分析具有较好的安全性和较强的抗JPEG压缩攻击能力。     

基于三维混沌系统的图像加密算法

为了改进图像加密算法的安全性和效率,提出了一种基于三维混沌系统和位运算的数字图像加密算法,利用三维混沌序列的坐标分量分别产生置换序列和二值序列,在对待加密图像进行预处理的基础上,先应用混沌置换序列对预处理的结果图像进行基于灰度值位序列的置换操作,然后再应用产生的二值序列对结果图像的灰度值位序列进行位异或加密运算。实验结果表明,该算法具有良好的安全性和加密效果。     

Chaotic maps based on binary particle swarm optimization for feature selection

Feature selection is a useful pre-processing technique for solving classification problems. The challenge of solving the feature selection problem lies in applying evolutionary algorithms capable of handling the huge number of features typically involved. Generally, given classification data may contain useless, redundant or misleading features. To increase classification accuracy, the primary objective is to remove irrelevant features in the feature space and to correctly identify relevant features. Binary particle swarm optimization (BPSO) has been applied successfully to solving feature selection problems. In this paper, two kinds of chaotic maps—so-called logistic maps and tent maps—are embedded in BPSO. The purpose of chaotic maps is to determine the inertia weight of the BPSO. We propose chaotic binary particle swarm optimization (CBPSO) to implement the feature selection, in which the K-nearest neighbor (K-NN) method with leave-one-out cross-validation (LOOCV) serves as a classifier for evaluating classification accuracies. The proposed feature selection method shows promising results with respect to the number of feature subsets. The classification accuracy is superior to other methods from the literature.     

基于Arnold变换和双混沌序列的二值图像置乱算法

提出一种基于Arnold变换和双混沌序列的二值图像置乱算法。首先使用Arnold变换扰乱像素间的逻辑联系,并使用中间截取法取得Logistic和Hybrid两个离散化的混沌序列中间序列部分,再用两个取得的序列与图像作“异或”处理来修改图像的像素值。仿真实验结果证明,该算法可有效地实现二值图像的加密,密钥空间大;加密后的图像,像素分布均匀,安全性好。     

Bit-level image cryptosystem combining 2D hyper-chaos with a modified non-adjacent spatiotemporal chaos

A novel bit-level image cryptosystem is proposed by introducing a new coupled map lattices (CML). The modified non-adjacent spatiotemporal chaotic system with good dynamic performance is constructed by coupling the piecewise-linear chaotic map (PWLCM) in a non-adjacent manner. In the proposed bit-level image cryptosystem, the binary plain image is scrambled globally by a 2D hyper-chaos system. And the confused image is then diffused via the pseudo-random sequences produced quickly and efficiently from the fabricative CML. After converting the diffused binary matrix into its homologous decimal matrix, the cipher image is achieved. Computer simulations and performance comparisons with recent image encryption algorithms demonstrate the superior performance and high security of our proposed cryptosystem.

     

A self-adaptive embedded chaotic particle swarm optimization for parameters selection of Wv-SVM

Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm driven by the simulation of a social psychological metaphor instead of the survival of the fittest individual. Based on the chaotic system theory, this paper proposes new PSO method that uses chaotic mappings for parameter adaptation of Wavelet v-support vector machine (Wv-SVM). Since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the proposed PSO introduces chaos mapping using logistic mapping sequences which increases its convergence rate and resulting precision. The simulation results show the parameter selection of Wv-SVM model can be solved with high search efficiency and solution accuracy under the proposed PSO method.     

A chaos-based image encryption algorithm using alternate structure

Combined with two chaotic maps, a novel alternate structure is applied to image cryptosystem. In proposed algorithm, a general cat-map is used for permutation and diffusion, as well as the OCML (one-way coupled map lattice), which is applied for substitution. These two methods are operated alternately in every round of encryption process, where two subkeys employed in different chaotic maps are generated through the masterkey spreading. Decryption has the same structure with the encryption algorithm, but the masterkey in each round should be reversely ordered in decryption. The cryptanalysis shows that the proposed algorithm bears good immunities to many forms of attacks. Moreover, the algorithm features high execution speed and compact program, which is suitable for various software and hardware applications.     

改进的混沌序列产生方法

为了得到具有良好随机性的二值序列,在已有方法的基础上,介绍了一种改进的混沌二值序列产生方法,该方法以混沌动力学模型为基础,利用非线性的方法产生混沌二值序列,实验表明产生的二值序列具有较好的随机性和初值敏感性,同时通过非线性的比较过程提高了算法的安全性.作为应用,还给出了该二值序列在图像加密中的应用.实验表明,该方法具有较好的效率和安全性.     

基于混沌序列和HVS的盲数字水印算法

提出一种针对彩色图像的基于混沌系统和人类视觉系统HVS(Human Visual System)的数字水印算法.通过该算法将二值水印经混沌系统加密后嵌入到彩色图像的蓝色分量B的小波系数中,在水印提取时根据密钥可以实现盲提取.实验结果表明,该算法对常用的图像处理如JPEG压缩、加噪、剪切和滤波等攻击具有较好的鲁棒性,取得了不可见性和鲁棒性的良好折中,同时盲检测使得水印检测的可靠性得到了很大的提高.     

A novel method for digital image steganography based on a new three-dimensional chaotic map

This paper, presents a novel chaos-based image steganography algorithm. Because of efficient property of chaos based security systems besides steganography applicability in providing secure communication, chaos based steganography algorithms served as a hot topic in recent researches. The proposed scheme possess novelties and advantageous such as: 1) Introducing a novel 3-dimensional chaotic map (LCA map) with strong chaotic characteristics and maximum Lyapunov exponent 20.58, which is used for generating three chaotic sequences, each of them represents the number of row, column, and colour component, respectively. 2) Utilizing random selection procedure for selecting subsequences with length of 2L, which L is the length of secret message 3) Specifying L pairs of triples host positions for embedding LSBs and MSBs of secret message by using three high level chaotic maps. 4) Entering some parameters dependent on elementary initial values, host image, and secret message features as a key point for adding additional layer of security alongside providing high sensitivity. 5) Providing high capacity for embedding secret message, which is equal to 50 % of whole image capacity (M?×?N?×?12). The proposed method could be applied in different criterion such as, confidential communication and data storing, protection of data alteration, and etc. Our experimental results guarantees that our scheme is not only robust against differential attacks, but also has promising results such as highly sensitive keys, Quality index, PSNR, MSE, and hiding capacity as shown in statistical security analysis.     

Period analysis of the Logistic map for the finite field

Usually, the security of traditional cryptography which works on integer numbers and chaotic cryptosystem which works on real numbers is worthy of study. But the classical chaotic map over the real domain has a disadvantage that the calculation accuracy of the floating point number can be doubled when the map is implemented by computer. This is a serious drawback for practical application. The Logistic map is a classical chaotic system and it has been used as a chaotic cipher in the real number field. This inevitably leads to the degradation of finite precision under computer environment, and it is also very difficult to guarantee security. To solve these drawbacks, we extend the Logistic map to the finite field. In this paper, we consider the Logistic map for the finite field N = 3ⁿ, and analyze the period property of sequences generated by the Logistic map over Z_N. Moreover, we discuss the control parameters which may influence the behavior of the mapping, and show that the Logistic map over Z_N may be suitable for application by performance analysis. Ultimately, we find that there exists an automorphic map between two Logistic maps with the different control parameters, which makes them suitable for sequence generator in cryptosystem. The automorphic sequence generated algorithm based on the Logistic map over Z_N is designed and analyzed in detail. These sequences can be used in the pseudorandom number generator, the chaotic stream cipher, and the chaotic block cipher, etc.     

The continuous artificial bee colony algorithm for binary optimization

Artificial bee colony (ABC) algorithm, one of the swarm intelligence algorithms, has been proposed for continuous optimization, inspired intelligent behaviors of real honey bee colony. For the optimization problems having binary structured solution space, the basic ABC algorithm should be modified because its basic version is proposed for solving continuous optimization problems. In this study, an adapted version of ABC, ABC_bin for short, is proposed for binary optimization. In the proposed model for solving binary optimization problems, despite the fact that artificial agents in the algorithm works on the continuous solution space, the food source position obtained by the artificial agents is converted to binary values, before the objective function specific for the problem is evaluated. The accuracy and performance of the proposed approach have been examined on well-known 15 benchmark instances of uncapacitated facility location problem, and the results obtained by ABC_bin are compared with the results of continuous particle swarm optimization (CPSO), binary particle swarm optimization (BPSO), improved binary particle swarm optimization (IBPSO), binary artificial bee colony algorithm (binABC) and discrete artificial bee colony algorithm (DisABC). The performance of ABC_bin is also analyzed under the change of control parameter values. The experimental results and comparisons show that proposed ABC_bin is an alternative and simple binary optimization tool in terms of solution quality and robustness.     

DisABC: A new artificial bee colony algorithm for binary optimization

Artificial bee colony (ABC) algorithm is one of the recently proposed swarm intelligence based algorithms for continuous optimization. Therefore it is not possible to use the original ABC algorithm directly to optimize binary structured problems. In this paper we introduce a new version of ABC, called DisABC, which is particularly designed for binary optimization. DisABC uses a new differential expression, which employs a measure of dissimilarity between binary vectors in place of the vector subtraction operator typically used in the original ABC algorithm. Such an expression helps to maintain the major characteristics of the original one and is respondent to the structure of binary optimization problems, too. Similar to original ABC algorithm, DisABC's differential expression works in continuous space while its consequence is used in a two-phase heuristic to construct a complete solution in binary space. Effectiveness of DisABC algorithm is tested on solving the uncapacitated facility location problem (UFLP). A set of 15 benchmark test problem instances of UFLP are adopted from OR-Library and solved by the proposed algorithm. Results are compared with two other state of the art binary optimization algorithms, i.e., binDE and PSO algorithms, in terms of three quality indices. Comparisons indicate that DisABC performs very well and can be regarded as a promising method for solving wide class of binary optimization problems.     

Robust fuzzy stabilization of dithered chaotic systems using island-based random optimization algorithm

Applying dither to highly nonlinear systems may suppress chaotic phenomena, but dynamic performance, such as convergence rate and disturbance attenuation, is usually not guaranteed. This paper presents a dithered H_∞ robust fuzzy control scheme to stabilize chaotic systems that ensures disturbance attenuation bounds. In the proposed scheme, Takagi-Sugeno (T-S) fuzzy linear models are used to describe the relaxed models of the dithered chaotic system, and fuzzy controllers are designed based on an extension to the concept of parallel distributed compensation (PDC). Sufficient condition for the existence of the H_∞ robust fuzzy controllers is presented in terms of a novel linear matrix inequalities (LMI) form which takes full consideration of modeling error and disturbances, but cannot be solved by the standard procedures. In order to solve the LMI problem and to identify the chaotic systems as T-S fuzzy modes, we propose a compound optimization strategy called the island-based random-walk algorithm (IRA). The algorithm is composed of a set of communicating random-walk optimization procedures concatenated with the down-hill simplex method. The design procedure and validity of the proposed scheme is demonstrated via numerical simulation of the dithered fuzzy control of a chaotic system.     

Sequences related to Legendre/Jacobi sequences

Two families of binary sequences are constructed from dth order cyclotomic generator and from dth order generalized cyclotomic generator with respect to two distinct primes respectively. By using estimates of certain exponential sums over rings or fields, the upper bounds of both the well-distribution measure and the order k (at least for small k) correlation measure of the resulting binary sequences are evaluated, and some lower bounds on the linear complexity profile of d-ary cyclotomic sequences and d-ary generalized cyclotomic sequences are presented. Our results indicate that such binary sequences possess “very good” local pseudo-randomness.