一种基于有向二分图模型和贝叶斯网络的入侵检测方法

针对入侵检测中存在的非确定性推理问题,文章提出一种基于二分图模型和贝叶斯网络的入侵检测方法,该方法利用二分有向图模型表示入侵和相关特征属性之间的因果拓扑关系,利用训练数据中获取模型的概率参数,最后使用最大可能解释对转化后的推理问题进行推理,并通过限定入侵同时发生的数目来提高检测效率。实验表明,该方法具有较高的检测率和很好的鲁棒性。     

Routing with multiple quality-of-services constraints: An approximation perspective

Finding a path that satisfies multiple Quality-of-Service (QoS) constraints is vital to the deployment of current emerged services. However, existing algorithms are not very efficient and effective at finding such a path. Moreover, few works focus on three or more QoS constraints. In this paper, we present an enhanced version of fully polynomial time approximation scheme (EFPTAS) for multiconstrainted path optimal (MCOP) problem. Specifically, we make four major contributions. We first allow the proposed algorithm to construct an auxiliary graph, through which the QoS parameters on each of the finding path can be guaranteed not to exceed the given constraints. Then we adopt a concept, called nonlinear definition of path constraints in EFPTAS for reducing both time and space complexity. Also, we enable EFPTAS to run iteratively to facilitate a progressive refinement of the finding result. In addition to these, we identify some “deployment” issues for proposed algorithm, the essential steps that how and when the EFPTAS takes place are presented. By analyzing the proposed algorithm theoretically, we find that the presented EFPTAS can find a (1+ε)-approximation path in the network with time complexity O(|E||V|/ε) (where |E| is the number of edges and |V| is the number of nodes), which outperforms the previous best-known algorithm for MCOP. We conduct an extensive comparison between the algorithm presented in this paper and previous best-known study experimentally, our results indicate that EFPTAS can find a path with low complexity and preferable quality.     

基于多信号流模型的模型封装与解包技术

随着科技的快速发展,设备系统的复杂程度越来越高,多信号流模型是系统测试性分析的常用模型,为解决复杂系统建模分析时对其各分系统信息保密问题,提出了一种基于多信号流模型的模型封装与解包方法。该方法首先确定了封装模块数据信息并实现封装,然后构建封装模块测试信息描述表,描述了封装模块内部故障、内部测试与外部信息的关系以及封装模块本身对外部信息的影响,实现了模块的解包。实验表明,该描述方法可以有效地屏蔽了被封装的分系统模型的技术信息,有利于各分系统设计者之间的信息保密,同时利用该描述方法,还可以有效地减少测试性分析所需的时间。     

压力容器CAD绘图软件包的研究

本文结合压力容器计算机辅助设计软件的研制,研究了利用AUTOCAD开发计算机辅助设计专用软件的几个关键性问题;主要有程序绘图,汉字信息、绘图数据的显示和选择以及与绘图程序的连接、专用软件的控制结构设计和内存管理等问题;提出了一整套设计新颖,使用方便,运行高效的解决方法。     

基于图像内容层次表征的遥感图像 分割方法

提出基于图像内容层次表征的高分辨率遥感图像快速多精度分割方法。首先根据初始分割结果建立区域邻接图(RAG),并将其定义为马尔可夫随机场(MRF);然后引入光谱、形状和边缘等图像特征进行层次合并,通过记录层次合并过程获得图像内容的层次表征;最后根据层次表征中不同层级对象之间的关系快速生成任意不同精度的分割结果,以满足不同应用的需求。利用QuickBird卫星图像进行实验和评价的结果表明,本文方法具有较高的精度和效率。     

带有局部控制因子的图割光流估计

提出一种带有局部空间项控制因子的图割光流估计算法,能判断和处理光流场的平移遮挡现象。文中分析了平移遮挡的形成机理,构造了遮挡判别公式,基于本次的正向和反向光流场,依靠遮挡判别结果调节局部空间项控制因子,建立下次的能量泛函,加强背景区域对遮挡区域的平滑作用,隔绝运动区域对遮挡区域的平滑作用,从而构造出新结构的网络流图。另外,该算法被证明可以阻断遮挡误判在各次图割优化过程间的传递,从而使逐次α-扩散移动图割光流算法具有自适应处理遮挡的能力。通过与Ground-truth光流场的实验对比,表明该算法能较好地判断与处理遮挡导致的光流场无效区域。     

基于攻击距离的攻击图优化方法

传统网络攻击图的生成随着网络规模扩大存在状态爆炸问题,网络安全管理员往往拿着冗余的攻击图不知所措。为了消除攻击图中不必要的攻击路径,保留下最优的攻击路径以供管理员防御参考,本文利用攻击距离对复杂的攻击图进行了优化。实验结果表明,利用此方法优化后的攻击图保留了最有可能的攻击路径,降低了攻击图的规模,随着网络规模的扩大,效果也越来越明显。     

基于最大加权独立集的频谱分配算法

动态频谱接入技术允许认知用户接入未授权的频谱,可以有效地提高频谱资源的利用率。频谱分配算法的时间开销和公平性是算法优劣的主要评价标准。本文从图论着色模型出发,构建了着色算法的评价体系及优化目标。针对用户间的公平性与分配的时间开销问题,在极大独立集的基础上提出了基于加权最大独立集的着色算法,获得了接近于最优的用户公平性,且该算法的时间开销等于信道数,与认知用户的数目无关。仿真分析验证了算法的正确性。     

On mapping processes to processors in distributed systems

This paper is concerned with the implementation of parallel programs on networks of processors. In particular, we study the use of the network augmenting approach as an implementation tool. According to this approach, the capabilities of a given network of processors can be increased by adding some auxiliary links among the processors. We prove that the minimum set of edges needed to augment a line-like network so that it can accommodate a parallel program is determined by an optimal path cover of the graph representation of the program. Anoptimal path cover of a simple graphG is a set of vertex-disjoint paths that cover all the vertices ofG and has the maximum possible number of edges. We present a linear time optimal path covering algorithm for a class of sparse graphs. This algorithm is of special interest since the optimal path covering problem is NP-complete for general graphs. Our results suggest that a cover and augment scheme can be used for optimal implementation of parallel programs in line-like networks.A preliminary version of this paper was presented at the 6th IEEE Conference on Computer Communications (INFOCOM '87).This reseach is supported in part by National Semiconductor (Israel), Ltd.     

Graph-Based Dimensionality Reduction for Hyperspectral Imagery: A Review

Hyperspectral image(HSI) contains a wealth of spectral information, which makes fine classification of ground objects possible. In the meanwhile, overly redundant information in HSI brings many challenges. Specifically, the lack of training samples and the high computational cost are the inevitable obstacles in the design of classifier. In order to solve these problems, dimensionality reduction is usually adopted. Recently, graph-based dimensionality reduction has become a hot topic. In this paper, the graph-based methods for HSI dimensionality reduction are summarized from the following aspects. 1) The traditional graph-based methods employ Euclidean distance to explore the local information of samples in spectral feature space. 2) The dimensionality-reduction methods based on sparse or collaborative representation regard the sparse or collaborative coefficients as graph weights to effectively reduce reconstruction errors and represent most important information of HSI in the dictionary. 3) Improved methods based on sparse or collaborative graph have made great progress by considering global low-rank information, local intra-class information and spatial information. In order to compare typical techniques, three real HSI datasets were used to carry out relevant experiments, and then the experimental results were analysed and discussed.Finally, the future development of this research field is prospected.