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Accurately identifying network traffics at the early stage is very important for the application of traffic identification.Recent years,more and more research works have tried to build effective machine learning models to identify traffics with the few packets at the early stage.However,a basic and important problem is still unresolved,that is how many packets are most effective in early stage traffic identification.In this paper,we try to resolve this problem using experimental methods.We firstly extract the packet size of the first 2-10 packets of 3 traffic data sets.And then execute crossover identification experiments with different numbers of packets using 11 well-known machine learning classifiers.Finally,statistical tests are applied to find out which number is the best performed one.Our experimental results show that 5-7are the best packet numbers for early stage traffic identification. 相似文献
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设备维修管理信息系统开发与应用 总被引:2,自引:0,他引:2
彭立志 《中国有色金属学报》1998,(Z2)
介绍了一个在微机网络上开发的设备维修管理信息系统,该系统将设备的维修计划与控制、设备状态与控制、维修费用、备件管理等有机地结合起来,建立了完整的计算机辅助管理系统。 相似文献
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文章借鉴CLIQUE聚类算法关于高维度数据空间单元划分的思想,将该思想引入到异常入侵检测中,并通过非均衡划分方法对该算法进行改进,力图建立一个对高维度入侵检测数据有效的异常检测模型。同时结合遗传算法,基于预定义的入侵检测数据集对高维度的入侵检测数据进行了数据维度约简的研究。 相似文献
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网格计算是基于网格结构的问题求解模式,它将网络上分布的计算机资源组织起来协同解决复杂的科学与工程计算问题。我们基于Globus项目的研究成果及其工具包,开发了面向水泥材料设计与仿真的网格系统。本文结合XML安全技术及水泥网格自身的特点。研究了网格结点间的信任体系和安全策略。提出了一种用将XML签名及XML加密技术应用于网格计算的方法。 相似文献
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Traffic classification research has been suffering from a trouble of collecting accurate samples with ground truth.A model named Traffic Labeller(TL) is proposed to solve this problem.TL system captures all user socket calls and their corresponding application process information in the user mode on a Windows host.Once a sending data call has been captured,its 5-tuple {source IP,destination IP,source port,destination port and transport layer protocol},associated with its application information,is sent to an intermediate NDIS driver in the kernel mode.Then the intermediate driver writes application type information on TOS field of the IP packets which match the 5-tuple.In this way,each IP packet sent from the Windows host carries their application information.Therefore,traffic samples collected on the network have been labelled with the accurate application information and can be used for training effective traffic classification models. 相似文献
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在互联网产生的早期阶段对其进行准确有效的识别,对于网络管理和网络安全来说都有着极其重要的意义。鉴于此,近年来越来越多的研究致力于仅仅基于流量早期的数个数据包,建立有效的机器学习模型对其进行识别。本文力图基于柔性神经树( FNT)构建有效的互联网流量早期识别模型。两个开放数据集和一个实验室采集的数据集用于实验研究,并将FNT与8种经典算法进行对比。实验结果表明,FNT在大多数情况下,其识别率和误报率指标优于其他算法,这说明FNT是一种有效的流量早期识别模型。 相似文献