一种粗糙集-决策树结合的入侵检测方法

针对入侵检测系统收集数据海量、高维、检测模型复杂和检测准确率低等问题,采用粗糙集属性约简的优势寻找与判断入侵与否相关的属性,利用决策树分类算法生成模型并对网络连接进行入侵预测分类检测,从而提出了一种粗糙集属性约简和决策树预测分类相结合的网络入侵检测方法.实验结果表明,该方法在入侵检测准确率上有很大的提高,对DoS攻击、Probe攻击和R2L攻击的检测效果均有所提高,同时大大降低了检测的误报率.     

一种改进的案例推理分类方法研究

特征属性的权重分配和案例检索策略对案例推理（Case-based reasoning,CBR）分类的准确率有显著影响. 本文提出一种结合遗传算法、内省学习和群决策思想改进的CBR分类方法. 首先,利用遗传算法得到多组属性权重,再根据内省学习原理对每组权重进行迭代调整;然后,通过案例群检索策略得到满足大多数原则的群决策分类结果;最后,以典型分类数据集的对比实验证明了本文方法能进一步提高CBR分类的准确率. 这表明内省学习可以保证权重分配的合理性,案例群检索策略能充分利用案例库的潜在信息,对提升CBR的学习能力有显著作用.     

基于特征相似度的贝叶斯网络入侵检测方法

传统贝叶斯入侵检测方法未考虑属性和属性权值对检测结果的影响。为此,提出基于特征相似度的贝叶斯网络入侵检测方法。利用相似度对网络连接数据的属性特征进行选择,抽取其关键特征,并降低属性的冗余度,以优化朴素贝叶斯的分类性能。实验结果表明,该方法能降低分类数据的维数,提高分类的准确率。     

基于互信息可信度的贝叶斯网络入侵检测研究

传统贝叶斯入侵检测算法没有考虑不同属性和属性权值对入侵检测结果的影响,因此分类准确率不够高.针对传统贝叶斯入侵检测算法存在的不足,提出基于互信息可信度的贝叶斯网络入侵检测算法.在综合考虑网络入侵检测数据特点和传统贝叶斯分类算法优点的基础上,用互信息相对可信度进行特征选择,删除一些冗余属性,把互信息相对可信度作为权值引进贝叶斯分类算法中,得到优化的贝叶斯网络入侵检测算法(MI-NB).实验结果表明,MI-NB算法能大大降低分类数据的维数,比传统贝叶斯入侵检测算法及改进算法有更高的分类准确率.     

基于决策树的网络连接类型预测

针对一个从模拟局域网中获取的数据集,设计并实现了一种基于决策树的连接类型预测工具;在一般决策树归纳算法的基础上,根据训练数据集的统计特征进行了预处理、改进和优化;对训练所得分类模型的准确率进行了评估,并通过实验考察了训练数据集大小和属性选择度量对结果的影响;也考虑了输入的测试数据存在的一些异常情况及解决办法.     

基于Na(i)ve Bayes分类的网络安全审计数据分析研究

研究了非监督学习Na(i)ve Bayes分类的原理和方法,并将其应用到文本数据--网络安全审计数据的分析中.为了提高分类准确率,根据分类的效果对数据的属性集进行选择,使用能提高分类准确性的属性作为分类的依据.对KDD CUP99数据集进行了基于不同属性集的实验,发现了与分类结果相关的属性,分类效果良好.     

共形预测框架下的高可靠入侵检测算法

入侵检测算法广泛应用于网络安全领域,然而现有基于机器学习的入侵检测算法仅输出数据的预测结果标签,缺少对预测结果置信值的评价机制,难以确保预测结果的可靠性。提出一种基于共形预测的高可靠入侵检测算法。将共形预测融入到传统机器学习算法中,得到数据分类标签和对应的置信值、可信度,提高网络数据分类的可靠性。通过对网络数据进行数字化、标准化和降维预处理,根据传统机器学习算法的特点,设计在共形预测框架下与各算法相对应的不一致得分计算公式,并引入平滑因子改进p-value的计算公式,使其能够以更平滑的方式计算预测结果p-value,提高算法的稳定性。实验结果表明,与单独采用SVM、DT和DT-SVM算法相比,该算法在KDD CUP99数据集上分类准确率分别提高11.1、4.6和3.7个百分点,在AWID数据集上分类准确率分别提高4.0、2.5和1.3个百分点,可保证入侵检测结果的高可靠性。     

C4.5算法对高血压病分类规则提取的研究

根据高血压病电子病历、实验室检查报告和医师处方数据,将C4.5决策树算法用于高血压分类规则的提取,挖掘出影响高血压病人血压值的重要因素。针对C4.5算法在属性选择方面的不足,引入相关度概念对算法做出改进,改进后的算法生成更合理和有效的分类规则,为高血压的分析预测提出了一种新的方法。     

多源头网络入侵特征的有效分类检测模型仿真

在多源头网络入侵检测的研究中,由于网络中接入不同协议的网络,造成入侵后很难确定入侵源头,传统入侵检测方法是根据单源网络确定入侵来源,进行入侵数据的确认,在多源网络中,无法确定入侵源头,导致多源头分布网络入侵检测模型的数据分类收敛效率低,检测准确率很低.提出了一种无约束聚类关联以及重复博弈因子的多源头网络入侵特征有效分类检测模型,面向多源头网络特征塑造多源头网络入侵模型,按照访问数据的辨识属性完善入侵检测模型,采用无约束聚类关联的入侵检测算法对网络多属性子干扰进行准确分类,在分类概率计算中融入约束计算博弈因子,采用数据博弈过滤网络入侵特征概率匹配过程中的多次概率对比,通过博弈约束计算最优反应函数,使得多源头网络入侵特征分类达到最优.仿真结果说明,所提模型可对网络入侵特征进行有效的分类,并且误检率和检测率都优于传统模型,具有明显的优化效果.     

基于无人机数据采样的人脸识别研究方法

提出了一种基于无人机数据采样的人脸识别研究方法。针对无人机采集的图像或视频数据进行人脸识别应用,采用深度学习算法对此进行研究,通过线下采集获取目标人脸,对采集到的目标人脸进行数据增强扩充数据集,进而增加人物识别准确率,使用训练好的Facenet网络对目标人脸进行特征提取,获得目标人物人脸特征并建立人脸特征库。在人脸检测阶段,当接收端接收到无人机采集的图像数据后,利用YOLOv5进行检测,识别人物所在区域,随后裁剪出人脸区域,传入Facenet网络进行人脸识别,获得采集到的人脸特征向量,然后结合人脸库与采集到的人脸特征向量。采用SVM进行数据分类,实现对不同类别的目标人物人脸分类,通过实验论证了此方法的可行性。     

煤矿井下安全监控分站的设计及其仿真实现

为了设计一种具有低成本、低功耗、易操作、功能强且可靠性高的煤矿井下安全分站,针对煤矿安全生产实际,文章提出了采用MCS-51系列单片机为核心、具有CAN总线通信接口的煤矿井下安全监控分站的设计方案;首先给出煤矿井下安全监控分站的整体构架设计,然后着重阐述模拟量输入信号处理系统的设计过程,最后说明单片机最小系统及其键盘、显示、报警、通信等各个组成部分的设计;为验证设计方案的可行性与有效性,使用Proteus软件对设计内容进行仿真验证,设计的煤矿井下安全监控分站具有瓦斯、温度等模拟量参数超标报警功能和电机开停、风门开闭等开关量指示功能;仿真结果表明:设计的煤矿井下安全监控分站具有一定的实际应用价值.     

View-based model-driven architecture for enhancing maintainability of data access services

In modern service-oriented architectures, database access is done by a special type of services, the so-called data access services (DAS). Though, particularly in data-intensive applications, using and developing DAS are very common today, the link between the DAS and their implementation, e.g. a layer of data access objects (DAOs) encapsulating the database queries, still is not sufficiently elaborated, yet. As a result, as the number of DAS grows, finding the desired DAS for reuse and/or associated documentation can become an impossible task. In this paper we focus on bridging this gap between the DAS and their implementation by presenting a view-based, model-driven data access architecture (VMDA) managing models of the DAS, DAOs and database queries in a queryable manner. Our models support tailored views of different stakeholders and are scalable with all types of DAS implementations. In this paper we show that our view-based and model driven architecture approach can enhance software development productivity and maintainability by improving DAS documentation. Moreover, our VMDA opens a wide range of applications such as evaluating DAS usage for DAS performance optimization. Furthermore, we provide tool support and illustrate the applicability of our VMDA in a large-scale case study. Finally, we quantitatively prove that our approach performs with acceptable response times.     

A pragmatic multi-method investigation of discrepant technological events: Coping,attributions, and ‘accidental’ learning

Discrepant technological events or situations that entail a problem, a misunderstanding or a difficulty with the Information Technology (IT) being employed, are common in the workplace, and can lead to frustration and avoidance behaviors. Little is known, however, about how individuals cope with these events. This paper examines these events by using a multi-method pragmatic approach informed by coping theory. The results of two studies – a critical incident study and an experiment – serve to build and test, respectively, a theoretical model that posits that individuals use a variety of strategies when dealing with these events: they experience negative emotions, make external attributions, and adopt engagement coping strategies directed at solving the event, eventually switching to a disengagement coping strategy when they feel they have no control over the situation. Furthermore, users’ efforts may result in ‘accidental’ learning as they try to overcome the discrepant IT events through engagement coping. The paper ends with a discussion of the results in light of existing literature, future opportunities for research, and implications for practice.     

The Distributed Time-Triggered Simulation Scheme: Core Principles and Supporting Execution Engine

Distributed real-time simulation is a young technology field but its practice is under increasing demands. In recent years the author and his collaborators have been establishing a new approach called the distributed time-triggered simulation (DTS) scheme which is conceptually simple and easy to use but widely applicable. The concept was initiated in the course of developing a new-generation object-oriented real-time programming scheme called the time-triggered message-triggered object (TMO) programming scheme. Some fundamental issues inherent in distributed real-time simulation that were learned during recent experimental studies are discussed along with some approaches for resolving the issues. An execution engine developed to support both the TMOs engaged in control computation and the TMOs engaged in DTS is also discussed along with its possible extensions that will enable significantly larger-scale DTSs.     

Software-Konfigurationsmanagement in großen Softwareprojekten

Zusammenfassung Mit zunehmender Größe der Softwaresysteme verschärfen sich die für die Software-Herstellung typischen Probleme: Beherrschen großer Objektmengen, Erhalten der Systemkonsistenz, Kontrolle der ständigen Änderungseinflüsse und Gewährleisten einer langen Lebensdauer. Die Disziplin Konfigurationsmanagement bildet den methodischen Ansatz, diese Probleme besser zu beherrschen. Software-Konfigurationsmanagement faßt die Herstellung von Softwaresystemen als eine Abfolge von kontrollierten Änderungen an gesicherten Zwischen- und Endergebnissen auf. Dargestellt werden die Objekte und Funktionen des Software-Konfigurationsmanagements sowie die hierfür in großen Software-Projekten benötigten Methoden, Instanzen und Hilfsmittel.     

Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and     

Editorial:Brain-machine interface(BMI) and cyborg intelligence

正Brain-machine interfaces(BMIs)aim at building a direct communication pathway between the brain and an external device,and represent an area of research where significant progress has been made during the past decade.Based on BMIs,mind information can be read out by neural signals to control     

Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and overseas to the world’s scientific circles,especially to stimulate     

SCIENCE CHINA Information Sciences SUBJECT INDEX TO VOLUME 57(2014)

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Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and overseas to the world’s scientific circles,especially to stimulate