基于模拟退火和半监督聚类的入侵检测方法

由于缺少监督数据,传统的基于聚类算法的入侵检测系统存在误报率高、检测率低等问题。针对这种情况,提出基于模拟退火和半监督K均值聚类的入侵检测方法。该方法首先利用少量标记入侵类型的网络数据改进聚类初始化过程,在K均值聚类算法中引入半监督学习,然后利用模拟退火算法跳出局部极值的能力与半监督K均值聚类算法结合以得到全局最优聚类,最后根据标记数据确定聚类类别,并应用于入侵行为的检测。基于KDDCUP99的对比实验表明,该方法利用监督数据和模拟退火算法改进了聚类算法,能够有效提高入侵检测的准确率。     

一种新的半监督入侵检测算法

针对无监督学习的入侵检测算法准确度不高、监督学习的入侵检测算法训练样本难以获取的问题,提出了一种粒子群改进的K均值半监督入侵检测算法,利用少量的标记数据生成正确样本模型来指导大量的未标记数据聚类,对聚类后仍未能标记的数据采用粒群优化的K均值聚类,有效提高分类器的分类准确性,并实现了对新类型攻击的检测。实验结果表明,算法的整体检测效果明显优于基于无监督学习和监督学习的检测算法。     

一种半聚类的异常入侵检测算法

针对基于监督学习的入侵检测算法所面临的训练样本不足的问题,提出了一种结合改进k 近邻法的基于半监督聚类的异常入侵检测算法,利用少量的标记数据改善算法的学习能力,并实现了对新攻击类型的检测。实验结果表明,在标记数据极少的情况下,算法的检测结果明显好于非监督学习的算法,接近于监督学习的检测算法。     

基于量子粒子群优化的网络入侵检测算法

提出了一种将量子粒子群优化算法和半监督模糊核聚类算法相结合的混合算法,用以解决入侵检测算法中模糊聚类算法对初始值敏感,容易陷入局部最优的问题。该算法对少量标记数据进行监督聚类得到正确模型,运用这个模型指导大量未标记数据进行聚类,扩充标记数据集合,对仍没有确定标记的数据利用量子粒子群优化的模糊核聚类算法进行聚类,确定其标记类型。通过KDD CUP99实验数据的仿真,实验结果表明,该算法在入侵检测中能获得理想的检测率和误检率。     

基于PSO-KM聚类分析的通信网络恶意攻击代码检测方法

恶意代码的快速发展严重影响到网络信息安全,传统恶意代码检测方法对网络行为特征划分不明确,导致恶意代码检测的结果不够精准,研究基于PSO-KM聚类分析的通信网络恶意攻击代码检测方法。分析通信网络中恶意攻击代码的具体内容,从网络层流动轨迹入手提取网络行为,在MFAB-NB框架内确定行为特征。通过归一化算法选择初始处理中心,将分类的通信网络行为特征进行归一化处理,判断攻击速度和位置。实时跟进通信网络数据传输全过程,应用适应度函数寻求恶意代码更新最优解。基于PSO-KM聚类分析技术构建恶意代码数据特征集合,利用小批量计算方式分配特征聚类权重,以加权平均值作为分配依据检测恶意攻击代码,实现检测方法设计。实验结果表明：在本文方法应用下对恶意攻击代码检测的正确识别率可以达到99%以上,误报率可以控制在0.5%之内,具有应用价值。     

基于半监督聚类的免疫入侵检测算法研究

传统的基于免疫的入侵检测系统需要足够的标记数据才能够生成具有良好泛化性能的抗体,而网络环境中获得充足的标记数据是困难的。为克服这一难题,对无监督聚类技术及免疫方法进行深入研究,并将二者结合起来,提出一种半监督的免疫入侵检测算法SCIID(Semi-supervised cluster based Immune Intrusion Detection)。在抗体产生阶段通过对自我样本进行聚类,大大缩短了阴性选择的时间;在入侵检测阶段采用聚类技术可快速获取未标记数据的类别,进而指导后续的学习过程,达到提高检测率的目的。仿真结果表明,该算法在仅有少量标记数据的情况下,可以获得大部分未标记数据的类别,而且能发现新的攻击类型,同等训练样例数目条件下检测率高于单纯基于免疫的方法。     

一种改进的半监督聚类入侵检测算法

针对网络环境,提出了一种新的半监督聚类入侵检测算法,将主动学习策略应用于半监督聚类过程中,利用少量的标记数据,生成用于初始化算法的种子聚类,通过辅助聚类过程,根据网络数据的特点,检测已知和未知攻击。主动学习策略查询网络中未标记数据与标记数据的约束关系,对标记数据可以快速获得k个不相交的非空近邻集,经检测结果证明,改进了算法的性能,且表明了算法的可行性及有效性。     

一种用于处理高维稀疏数据的半监督聚类算法

半监督聚类是近年来研究的热点,传统的方法是在无监督算法的基础上加入有限的背景知识来提高聚类性能.然而大多数半监督聚类技术都基于邻近或密度,难以处理高维数据,因此必须将约减的特征加入到半监督聚类过程中.为解决此问题,提出了一种新的半监督聚类算法框架.该算法利用样本约束传递性进行预处理,然后将特征投影到低维空间实现降维,最终用半监督算法对约减后的样本进行聚类.通过实验同现行主要降维方法进行了比较,说明此方法能有效地处理高维数据,聚类效果良好.     

基于Tri-Training和数据剪辑的半监督聚类算法

提出一种半监督聚类算法,该算法在用seeds集初始化聚类中心前,利用半监督分类方法Tri-training的迭代训练过程对无标记数据进行标记,并加入seeds集以扩大规模;同时,在Tri-training训练过程中结合基于最近邻规则的Depuration数据剪辑技术对seeds集扩大过程中产生的误标记噪声数据进行修正、净化,以提高seeds集质量.实验结果表明,所提出的基于Tri-training和数据剪辑的DE-Tri-training半监督聚类新算法能够有效改善seeds集对聚类中心的初始化效果,提高聚类性能.     

基于量子人工鱼群和模糊核聚类算法的网络入侵检测模型研究

针对基于传统模糊C均值聚类的网络入侵检测模型存在分类效果不佳,且容易出现局部极值的问题,提出了一种基于量子人工鱼群的半监督模糊核聚类算法。该算法使用少量的标记数据和大量未知标记数据生成网络入侵检的分类,并通过核距离的方式构建了模糊C均值聚类算法的新目标函数,此外,结合了量子人工鱼群算法来解决模糊核聚类算法的全局最优解问题,适用于并行执行架构。在KDD Cup 99网络入侵检测数据上的仿真实验结果表明,相比于基于FCM和PSO-FCM的入侵检测模型,以及基于此提出的算法入侵检测模型具有更好的检测率。     

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。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.