一种基于粗糙集理论和BP神经网络的入侵检测新方法

针对入侵检测数据存在维数大、冗余度高及噪声数据较多的缺陷,结合粗糙集理论和BP神经网络在数据处理方面的优势,提出了一种入侵检测新方法(RSBP). RSBP利用粗糙集理论进行数据约简时,为得到一组最小相对约简,提出一种基于遗传算法的属性约简算法.将简化的数据集作为BP网络的输入数据,可以简化BP网络的结构、缩短训练时间且提高了BP网络分类准确率.通过实验将RSBP与基于主成分分析(PCA)和BP网络的入侵检测方法(PCABP)做比较,实验结果表明,RSBP的训练时间更短、检测的准确率更高.     

基于粗糙集的网络入侵检测模型研究

本文提出了一种基于粗糙集(Rough Set)理论的网络入侵检测模型,通过运用粗糙集理论结合遗传算法对网络连接数据提取检测规则集。仿真结果表明,该方法对各类已知和未知攻击尤其是DoS和Probe攻击具有较高的检测率和较低的误报率,因此本文提出的基于粗糙集理论的入侵检测模型在应用于复杂网络数据分析和网络攻击检测方面是高效的。     

粗糙集-遗传算法在入侵检测系统中的研究与应用

本文提出一种基于遗传算法和粗糙集理论集合的入侵检测的新方法。该方法成功地把遗传-粗糙集理论引入到入侵检测中,提出了基于粗糙集-遗传算法理论的网络入侵检测方法,应用混合遗传算法求解粗糙集的约简,减少了计算时间。实验结果表明,该方法对不同类型的网络攻击具有很高的检测率和较低的误检率。     

基于模糊粗糙集属性约简与GMM-LDA最优聚类簇特征学习的自适应网络入侵检测

网络入侵方式已日趋多样化,其隐蔽性强且变异性快,开发灵活度高、适应性强的实时网络安全监测系统面临严峻挑战.对此,提出一种基于模糊粗糙集属性约简(FRS-AR)和GMM-LDA最优聚类簇特征学习(GMM-LDA-OCFL)的自适应网络入侵检测(ANID)方法.首先,引入一种基于模糊粗糙集(FRS)信息增益率的属性约简(AR)方法以实现网络连接数据最优属性集选择;然后,提出一种基于GMM-LDA的最优聚类簇特征学习方法,以获得正常模式特征库和入侵模式库的最优特征表示,同时引入模式库自适应更新机制,使入侵检测模型能够适应网络环境动态变化.KDD99数据集和基于Nidsbench的网络虚拟仿真实验平台的入侵检测结果表明,所提出的ANID方法能有效适应网络环境动态变化,可实时检测出真实网络连接数据中的各种入侵行为,其性能优于当前常用的入侵检测方法,应用前景广阔.     

基于快速属性约简的网络入侵特征选择

高维网络数据中的无关属性和冗余属性会导致入侵检测速度慢及效率低下。为解决该问题,提出一种基于快速属性约简的网络入侵特征选择方法。以网络数据的条件属性与类别属性之间的互信息为度量去除无关属性,采用基于粗糙集正区域的属性重要性计算公式作为启发信息,设计一种快速属性约简算法去除网络数据的冗余属性,实现网络入侵特征子集的优化选择。在KDD CUP1999数据集上的仿真实验结果表明,该方法能有效去除网络数据中的无关属性和冗余属性,具有较高的入侵检测率和较低的误报率。     

基于信息熵rough set的多层凝聚入侵检测算法

针对大数据量的入侵检测算法计算复杂度过高的问题,提出一种基于信息熵rough set的多层凝聚入侵检测算法。首先,利用粗糙集对入侵检测数据进行预处理和属性约简,防止算法陷入“维数陷阱”;其次,用粗糙集熵重要测度权重距离代替多层凝聚算法的欧式距离计算个体相似度,实现粗糙集预处理与多层凝聚算法的对接;最后,通过实验表明,基于信息熵rough set的多层凝聚入侵检测算法能够更有效的对入侵数据进行检测。     

基于粗糙集的进化神经网络入侵检测系统研究

针对目前实时入侵检测系统所处理的网络数据具有的非线性和高维的特点,提出基于粗糙集理论的进化神经网络入侵检测方法。对网络中截获的数据,利用粗糙集属性约简方法对其属性集进行约简,得到影响分类精度的重要属性。把约简后形成的训练样本进行数值化和归一化处理,作为神经网络的输入数据,再利用遗传算法较强的宏观搜索能力和全局寻优的特点,优化神经网络权值,并在此基础上进行神经网络学习,从而建立入侵检测系统的优化分析模型。实验结果表明,该算法学习速度快,有效提高了入侵检测系统的检测效率。     

基于信息增益和粗糙集的入侵检测方法

传统的随机森林在网络入侵检测中收敛速度慢,并且学习性能不够完善。为消除原始入侵检测数据中的冗余信息,提出一种基于信息增益和粗糙集的随机森林入侵检测方法。使用信息增益对数据的各个属性进行相关分析,删除冗余属性,减小属性简约的时间复杂度;利用粗糙集理论从数据中提取分明函数,求得属性简约;使用随机森林分类器进行分类。实验结果表明,该方法收敛速度较快,在召回率和精度方面都要高于传统的随机森林方法,尤其是在训练样本充足的网络环境下,效果更加明显。     

基于熵重要测度权重粗糙集的阿尔法多层凝聚入侵分类

针对入侵检测数据量大,而文献[1]提出的α核心集的多层凝聚算法计算复杂度过高,影响实际应用的问题,提出一种基于熵重要测度权重粗糙集的α核心集多层凝聚入侵分类算法。首先,基于熵重要测度权重方法利用粗糙集对入侵检测数据进行预处理和属性约简,降低数据维数防止算法陷入"维数陷阱";其次,用熵重要测度权重距离代替阿尔法多层凝聚算法的欧式距离计算个体相似度,并实现粗糙集输出数据与阿尔法多层凝聚算法的有效对接。通过实验表明,基于熵重要测度权重粗糙集的α核心集多层凝聚入侵分类算法能够更加有效对KDD CUP 99标准数据库进行检测分类。     

基于机器学习与大数据技术的入侵检测方法研究

为有效检测网络的攻击行为,提出了基于机器学习与大数据技术的入侵检测方法。首先分析当前网络入侵检测算法,描述了大数据分析技术的网络入侵原理,然后将GRU神经网络与SVM分类算法相结合,最后使用网络入侵检测数据集进行实验。实验结果表明基于GRU-SVM模型的网络入侵检测成功率高于其他模型,网络入侵检测整体效果得到改善,保证...     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

基于QTE的蒙古文显示机制研究与实现

蒙古语言是中国蒙古族使用的通用语言,由于蒙古文区别于其他文字的书写方式和其自身变形机制等特点,在很多通用的文字处理引擎中都不被支持。在嵌入式产品开发与应用领域中Linux加QTE已经成为流行方式。该文给出了一种在QTE环境上实现基于标准Unicode的蒙古文点阵显示和变形算法, 并自定义了支持蒙古文的QTE组件,扩展了QTE功能,为在Linux加QTE方式的嵌入式体系结构中处理蒙古文提供了一种解决方法。