新的不可否认门限代理签名方案

对文献的门限代理签名方案进行了密码分析,发现该方案不能抵抗内部攻击和公钥替换攻击.提出了一个新的安全高效的不可否认门限代理签名方案,新方案克服了原方案的缺点,不仅能够抵抗内部攻击、公钥替换攻击和合谋攻击,而且满足安全门限代理签名方案的安全要求,可以在公开信道中进行.     

一种门限代理签名方案的安全性分析及改进

对Hu等人改进的一种门限代理签名方案(J-H-J-Z方案)进行了安全性分析,发现该方案存在漏洞,容易受到证书攻击:伪造原始签名人,并且不具备不可否认性.针对以上问题对该方案进行了改进,改进后的方案克服了原方案的特点,提高了系统的安全性,并保留了原方案的一些优点.     

一种基于智能卡的增强型身份鉴别方案

在分析现有的基于智能卡身份鉴别方案安全缺陷的基础上,提出了一种增强的身份鉴别方案.该方案不但能够保留现有身份鉴别方案的优点,而且能够很好的抵抗拒绝服务攻击,离线字典攻击和重放攻击.     

NTRU密钥体制的攻击补偿与攻击判定

本文简要分析了NTRU发生解密错误的原因,借由针对解密错误的纠错补偿算法,提出一种用于扩大攻击可行域的补偿算法。以NTRU在解决解密错误的协议层方案为基础,提出对攻击结果进行判定的方法,最后用一个具体实例进行说明上述方法的有效性。     

一种针对OLSR协议典型攻击的有效防御机制

分析了自组网中OLSR(Optimized Link State Routing Protocol)路由协议的脆弱性以及它可能遭受的各种攻击.针对这些潜在的攻击,将公钥机制和信任模型结合,提出了一种防御方案,该方案结合了以反应式PKI为基础进行的公钥签名和信任评价机制,并阐述了如何通过该防御机制有效地防御攻击,最后,用NS仿真工具对该防御机制进行了仿真,并论证了防御方案的可行性.     

中间人攻击下增强身份保护的IKEv2改进

首先探讨了IKEv2协议可能遭受中间人攻击和密钥生成方案面临蜕化消息攻击的缺陷,针对退化消息攻击的威胁提出了基于共享密钥的密钥生成方案.针对存在的身份保护缺陷进行了分析,并相应地对IKEv2协议进行改进,提出的方案能够有效地进行身份保护.改动后的实现代价并不大,也不破坏ISAKMP框架及交换的对称性.     

一种基于椭圆曲线自双线性映射的多秘密共享方案

分析了Duo Liu等人提出的基于椭圆曲线自双线性映射的多秘密共享方案,发现该方案易遭受分发者/参与者欺诈攻击和广播窃听攻击,并依赖安全信道;提出了一种基于单向散列函数、密钥协商协议和动态多方Deffie-Hellman协议的改进方案,改进方案能抵抗分发者/参与者欺诈攻击和广播窃听攻击,并使方案摆脱对安全信道的依赖.最后对改进方案的安全性进行了分析.     

B／S 架构下基于会话指纹的同源重放攻击应对方案研究

针对采用“内网IP地址＋NAT”接入互联网形成的内网中容易发生同源重放攻击的问题，通过引入会话指纹（ Session Fingerprinting）的概念，提出了基于会话识别的同源重放攻击应对方案。该方案通过会话指纹，识别会话的变化，适时地要求用户输入原始认证信息，例如，用户名和密码，进行身份认证，达到应对重放攻击的目的。代码实现和理论分析均表明，提出的应对方案能够有效地应对同源重放攻击。     

一种基于软令牌的企业即时通信双向认证方案

为了提高EIM(Enterprise Instant Messenger)的安全性,在对比当前常用认证技术的基础上,提出了一种结合HASH函数、对称密码机制以及挑战/应答机制的基于软令牌的双向认证方案.最后对该方案进行了性能分析.结果表明:该方案具有保护用户身份信息,防止诸如重放、假冒和穷举等常见身份认证攻击,实现双向...     

一种改进的iTrace技术的研究

针对现有ICMP反向追踪方法中iTrace信息标记的IP地址或相关信息,导致重构完整攻击路径需要过多的数据包,并且计算量大的问题,提出了在iTrace分组中重新编码的方案。该方案可在较短的时间内推算出主要攻击路径,显著减少路径重构时对数据包的需求量,从而可以使受害者更快捷地追踪到攻击源,为受害者尽快响应攻击、减少攻击带来的损失创造了条件。     

热镀锌板线状缺陷分析方法探讨

以热镀锌板为测试材料,采用表面直接观察、截面观察和表面脱镀层观察等方法对其线状缺陷进行研究,并通过SEM、EDS分析对其线状缺陷形貌和组成进行表征。结果表明,采用这些方法可判定热镀锌板线状缺陷产生的原因,从而为使其产品表面缺陷得到有效控制提供依据。     

Application of improved back-propagation algorithms in classification and detection of scars defects on rails surfaces

An experimental platform with bracket structures,cables,parallel computer and imaging system is designed for defects detecting on steel rails. Meanwhile,an improved gradient descent algorithm based on a self-adaptive learning rate and a fixed momentum factor is developed to train back-propagation neural network for accurate and efficient defects classifications. Detection results of rolling scar defects show that such detection system can achieve accurate positioning to defects edges for its improved noise suppression. More precise characteristic parameters of defects can also be extracted.Furthermore,defects classification is adopted to remedy the limitations of low convergence rate and local minimum. It can also attain the optimal training precision of 0. 00926 with the least 96 iterations. Finally,an enhanced identification rate of 95% has been confirmed for defects by using the detection system. It will also be positive in producing high-quality steel rails and guaranteeing the national transport safety.     

Improved Genetic Algorithm Application in Textile Defect Detection

Based on an efficient improved genetic algorithm, a pattern recognition approach is represented for textile defects inspection. An image process is developed to automatically detect the drawbacks on textile caused by three circumstances： break, dual, and jump of yams. By statistic method, some texture feature values of the image with defects points can be achieved. Therefore, the textile defects are classified properly. The advanced process of the defect image is done. Image segmentation is realized by an improved genetic algorithm to detect the defects. This method can be used to automatically classify and detect textile defects. According to different users＇ requirements, different types of textile material can be detected.     

系统结构缺陷分层预测方法

为解决缺陷预测中的缺陷分类问题, 提出了分层式缺陷预测模型。通过对缺陷特征的分析建立了缺陷特征预测方法, 使具有相似特征的缺陷形成相似特征缺陷簇。给出了相似特征缺陷簇间关联关系预测方法, 构建了缺陷关联关系预测模型, 使具有强关联关系的相似特征缺陷簇再次成簇, 从而达到缺陷预测的目的。实验结果表明, 在缺陷成簇密度、 成簇数量及成簇客观性方面, 该系统结构缺陷分层预测方法好于K-means算法。     

基于ISODATA算法的漏磁信号到缺陷轮廓的网络映射

由于漏磁信号与缺陷轮廓的非线性关系，由管道漏磁信号描述管道缺陷的几何特征一直是管道漏磁检测的难点．本采用小波基函数神经网络的方法，建立了由管道缺陷的漏磁信号到缺陷截面轮廓图的网络映射．算法中应用迭代自组织数据分析(ISODATA)动态聚类的算法使得基函数中心的选取更加合理，经过多层分辨率的训练．网络输出表明，该网络可以较准确反映出缺陷的几何特征，为管道缺陷的特征提取提供一种可行的方法。     

Improved Roberts operator for detecting surface defects of heavy rails with superior precision and efficiency

An experimental platform accompanying with the improved Roberts algorithm has been developed to achieve accurate and real-time edge detection of surface defects on heavy rails.Detection results of scratching defects show that the improved Roberts operator can attain accurate positioning to defect contour and get complete edge information.Meanwhile,a decreasing amount of interference noises as well as more precise characteristic parameters of the extracted defects can also be confirmed for the improved algorithm.Furthermore,the BP neural network adopted for defects classification with the improved Roberts operator can obtain the target training precision with 98 iterative steps and time of 2s while that of traditional Roberts operator is 118 steps and 4s.Finally,an enhanced defects identification rate of 13.33%has also been confirmed after the Roberts operator is improved.The proposed detecting platform will be positive in producing high-quality heavy rails and guaranteeing the national transportation safety.     

基于Wold纹理模型和分形理论的织物疵点检测

应用基于Wold纹理模型,从织物纹理中提取非确定性随机结构.通过正常纹理和疵点纹理中随机结构的表面维分形特征曲线比较,以距离为判别标准定位疵点.几种典型织物疵点的分析表明,基于Wold纹理模型和分形理论的分析方法能准确地检测出织物表面的多种疵点.     

工业X光图像安全检测算法

在工业X光图像安全检测中，缺陷在某种尺度下可以看作是屋脊边缘。从多尺度边缘检测的角度分析得出：在一定尺度下，圆形缺陷在两个方向上都看作是屋脊边缘，而条形缺陷只在一个方向上被看作是屋脊边缘。利用小波多尺度边缘检测的两个分量来确定两个方向是否都存在屋脊边缘，从而区分开这两种形状缺陷。使用LOG算子提取圆形缺陷，使用方向可调滤波器提取条形缺陷，根据检测到的缺陷的形状参数来对缺陷进行分类判级。实验表明，该算法有很好的检测效果。     

BGA焊点空洞缺陷的数学形态学分析

BGA焊点焊接过程中容易产生气泡,形成空洞缺陷,检测时如何自动分析一直是个难题。提出使用Otsu算法分割焊球,使用数学形态学中的开闭运算、顶帽变换提取空洞缺陷的技术方案,实现每个焊点空洞缺陷的准确提取和自动分析。实验结果表明,提出的技术方案鲁棒性强,可应用于BGA焊点的空洞缺陷检测。     

Image boundary extraction based on island model genetic algorithms for integrated circuit defect detection

The integrated circuit chip with high performance has a high sensitivity to the defects in manufacturing environments. When there are defects on a wafer, the defects may lead to the degradation of chip performance. It is necessary to design effective detection approaches for the defects in order to ensure the reliability of wafer. In this paper, a new method based on image boundary extraction is presented for the detection of defects on a wafer. The method uses island model genetic algorithms to perform the segmentation of wafer images, and gets the optimal threshold values. The island model genetic algorithm uses two distinct subpopulations, it is a coarse grain parallel model. The individuals migration can occur between the two subpopulations to share genetic materials. A lot of experimental results show that the defect detection method proposed in this paper can obtain the features of defects effectively.