一种针对弹性CA的分布式密钥产生方案

弹性CA是一种使用入侵容忍技术保护CA密钥的CA系统,它采用了新的私钥分割方法加强了系统的安全性,但其使用的密钥分发中心却不利于CA私钥安全 .分布式密钥产生方案就是在传统的弹性CA方案的基础上取消了密钥分发中心,使用分布式的密钥产生和分割机制,从而保证了在CA初始化和整个运行过程中,任意t-1(t为门限值)台服务器都不可能窃得CA私钥,大大加强了CA系统安全 .     

Identification of the neighborhood and CA rules from spatio-temporal CA patterns

Extracting the rules from spatio-temporal patterns generated by the evolution of cellular automata (CA) usually produces a CA rule table without providing a clear understanding of the structure of the neighborhood or the CA rule. In this paper, a new identification method based on using a modified orthogonal least squares or CA-OLS algorithm to detect the neighborhood structure and the underlying polynomial form of the CA rules is proposed. The Quine-McCluskey method is then applied to extract minimum Boolean expressions from the polynomials. Spatio-temporal patterns produced by the evolution of 1D, 2D, and higher dimensional binary CAs are used to illustrate the new algorithm, and simulation results show that the CA-OLS algorithm can quickly select both the correct neighborhood structure and the corresponding rule.     

基于形态学和坐标变换的二维CA图像处理技术研究

深入研究了一类二维细胞自动机(CA)，提出了一种用于二值和多值图像处理的二维CA实现方法。对于二值图像，提出了类似于数学形态学腐蚀、膨胀的CA布尔逻辑规则；对于多值图像，采用坐标逻辑运算把图像分解成爹个二值图像后用CA并行处理。所有的CA规则都可以用细胞神经网络(CNN)实现。最后，将这种方法用于图像滤波，获得了很好的实验结果。     

容忍入侵的CA方案设计与实现

为了提高联网(certificate authority,CA)的安全性,基于(t,n)秘密共享思想,引入安全芯片及RSA分步签名方法,提出了一种具有容忍入侵能力的CA方案。新提出的CA方案从算法理论和系统架构两方面着手,克服传统CA的安全缺陷,保证CA私钥在产生、拆分和分步签名时的安全性,有效地解决了CA抵抗内外部攻击问题,确保了联网CA系统具有一定的入侵容忍能力。最后通过C++和OpenSSL实现了CA系统,验证了该CA方案的可行性。     

Correspondence Analysis: A New Method for Analyzing Qualitative Data in Architecture

This article aims at establishing a new application of the correspondence analysis (CA) method for analyzing qualitative data in architecture and landscape architecture. This method is primarily used in genealogy but is here, for the first time, applied to architectural studies. After introducing a qualitative method based on coding process, a practical guide for using CAQDAS (Computer-Assisted Qualitative Data Analysis Software) is provided. The software NVivo-8 is applied to analyze the data. CA, a multivariate statistical technique, is used to identify the underlying structure of the data and visualize the results. For the purpose of testing this method in practice, the National Garden of Tehran was selected as a case study to provide the data. The focus is on visualizing the similarities between the properties of the National Garden of Tehran and several different garden design styles. Two reliability tests were performed to verify the results, indicating that the National Garden of Tehran has many characteristics similar to those of a typical Baroque garden style. We believe that this new method may have wide application possibilities for studies on architecture, urban design, and landscape architecture.     

一种基于秘密分享的认证中心私钥保护方案

针对CA私钥的高安仝性需求,提出一种新的(t,n)秘密分享机制保护CA私钥.首先,使用RSA算法产生CA私钥,保证了私钥的不可伪造性:然后基于新的(t,n)秘密共享机制将CA私钥进行分存,使用其身份作为私钥份额的标识,并使用私钥作为秘密份额.在使用CA私钥进行签名时,使用Lagrange插值多项式进行重构,并提供了简单...     

A new fast cellular automata orthogonal least-squares identification method

A novel fast cellular automata orthogonal least squares (FCA-OLS) identification method is introduced by extending and developing the CA-OLS identification method presented in a previous study by Billings and Yang. Both one-dimensional CA and two-dimensional CA were identified with FCA-OLS as the simulation examples. The simulation results show that the new method significantly reduces the computational time compared with existing methods.     

一种新的基于模糊逻辑的CFAR检测器

基于模糊逻辑,无偏最小方差估计(UMVE)和单元平均(CA)提出一种新的恒虚警检测器(FUCAP)。它的前、后沿滑窗分别采用模糊UMVE方法和模糊CA方法得到映射到虚警空间的两个隶属函数值,再将这两个值相乘作为检测统计量。分析结果表明,FUCAP在均匀背景和多目标环境下均具有不错的检测性能。     

对细胞神经网络字符图像平滑技术的研究

深入研究了一种二维细胞自动机(CA),找到了两个算法规则可以用来实现二值字符平滑和图像去噪处理,并且用这些规则设计了三种新的细胞神经网络(CNN)．仿真结果证明这些CNN是简单而有效的,同时也证明了文中算法的合理性,为CNN的设计找到了一种新颖、有效的方法．     

虚拟企业的安全交互模型

虚拟企业是由异构企业组成的临时动态联盟，在实际的运作中与普通企业有很大的不同，现有的各种企业CA信任模型(如等级模型、对等模型等)都无法适应虚拟企业安全交互的需求，而虚拟CA，即：VCA，为虚拟企业的安全交互提供了一种新的方法和思路，针对原有VCA方案的不足和缺陷，并结合两个虚拟企业的典型实际案例，分析出虚拟企业的主要特点和要求，由此构建了新的VCA模型，并提出了此VCA模型的比较完整的安全解决方案。     

自组织网络中基于ID加密的自启动分布式CA

本文针对自组织网络无中心、易受攻击等特点提出了一种基于ID加密的自启动分布式CA模型,讨论了自组织网络中基于ID加密的自启动分布式CA的形成,密钥更新,对入网节点的阈值签名,以及入网节点自身分钥/私钥对的产生过程。     

基于PKI的CA认证系统信任模型的研究

在PKI体系中,CA之间的信任关系是一个极为重要的部分,建立相应的信任模型是认证系统中一个必须解决的问题。本文通过分析PKI系统结构和工作原理,并且比较了几种常见的CA信任模型的结构特性和使用范围,提出了一种在适用于校园网认证系统中的新型的CA信任模型。与常见的模型相比,这种复合式的新模型有着更为快捷和灵活的认证路径,更全面的安全机制,和更为方便的扩展能力,因此也更适用于目前较为复杂多变的大型网络环境中。     

新的进化算法--文化算法

文化算法源于对人类社会多层面进化的模拟,为进化算法提供了一个新的计算框架.和其他进化算法相比,文化算法概念清晰,更能准确地反映社会的进化过程,并在一些领域取得了成功的应用.本文首先讲述了该算法的生物解释,然后介绍了算法的基本原理和不同版本,并给出了一些成功应用的实例,最后给出了本文的结论和进一步的研究方向.     

基于模糊逻辑的多速率WLAN自适应MAC协议

针对DCF应用在多速率无线局域网中存在吞吐量异常和严重不公平性问题,提出了一个基于信道状态和节点速率的模糊自适应退避算法——RCFAB算法。仿真结果表明,RCFAB能够适应多速率WLAN,并有效地改善系统的吞吐量和接入公平性。     

改进元胞蚂蚁模型在路径规划中的应用

将地图离散化处理是移动机器人的摄像头传感器的通用方式。元胞自动机理论是一种适合复杂大系统模拟的工具,其时间、空间和状态都离散;而蚁群算法是解决离散优化问题的成熟理论。元胞蚁群模型是结合元胞理论和蚁群算法的一种新路径规划方法。实验表明：这种新方法可行且有效。     

Learning cellular automata rules for binary classification problem

This paper proposes a cellular automata-based solution of a binary classification problem. The proposed method is based on a two-dimensional, three-state cellular automaton (CA) with the von Neumann neighborhood. Since the number of possible CA rules (potential CA-based classifiers) is huge, searching efficient rules is conducted with use of a genetic algorithm (GA). Experiments show an excellent performance of discovered rules in solving the classification problem. The best found rules perform better than the heuristic CA rule designed by a human and also better than one of the most widely used statistical method: the k-nearest neighbors algorithm (k-NN). Experiments show that CAs rules can be successfully reused in the process of searching new rules.     

一种应用主导的CA互通技术

研究了一种新的以应用为主导的CA互通技术数字证书本地认证技术。从应用的角度来解决CA的互联互通问题,弥补了现有CA互通 技术的一些不足。     

Applying lightweight directory access protocol service on session certification authority

Lightweight Directory Access Protocol (LDAP) service is a new technology being applied on the Internet. On large-scale network systems using Transmission control protocol (TCP)/Internet protocol (IP), there is no standard suggested for single directory––certainly without one to be routinely used on the scale of intranets. LDAP service has many great features, such as providing quick and advanced search, quick response and hierarchy view of data. It also can be utilized to many different applications.Certification Authority (CA) is a trusted system, and it plays an important role just like a notary bridging between end-entities and helps end-entities to establish a secure environment. If someone wants to trade or communicate with others, he or she needs the certificate issued by the CA to help him or her get the trust from others. When a number of end-entities need this service, the load of CA may become huge. Using distributed CAs may sound like a good idea, but it costs too much. In this paper, we have designed a Session CA using a directory system to share its load without the necessity to maintain the Certificate Revocation List (CRL) because the lifetime of the attribute certificate is very short.With these great features of LDAP service mentioned above, it becomes desirable that we can apply them to design a new CA system. By using LDAP service, we can reduce the load of certification significantly between CA and end-entity. In addition, this new technology can reduce the maintenance work of administration and improve the efficiency of our new proposed CA. Furthermore, combining with Role-Based Access Control (RBAC) and attribute certificate, the security of our system is greatly improved.     

Research of neural network algorithm based on factor analysis and cluster analysis

Aiming at the large sample with high feature dimension, this paper proposes a back-propagation (BP) neural network algorithm based on factor analysis (FA) and cluster analysis (CA), which is combined with the principles of FA and CA, and the architecture of BP neural network. The new algorithm reduces the feature dimensionality of the initial data through FA to simplify the network architecture; then divides the samples into different sub-categories through CA, trains the network so as to improve the adaptability of the network. In application, it is first to classify the new samples, then using the corresponding network to predict. By an experiment, the new algorithm is significantly improved at the aspect of its prediction precision. In order to test and verify the validity of the new algorithm, we compare it with BP algorithms based on FA and CA.