学术
基于特征加权的故障征兆处理算法
崔中杰[1,2] 姚淑萍[1,3] 唐成华[1,2]
[1]北京理工大学网络攻防对抗技术实验室,北京100081 [2]北京理工大学机电工程学院,北京100081 [3]北京理工大学软件学院,北京100081
摘 要:
为了防范网络中存在的多种多样的安全威胁。由大量并构型安全设备所组成的统一管理平台得到了广泛地应用。然而如何有效地解决由这些安全设备集成所引发的各种冲突和故障，已成为网络管理的重点和难点。提出以距离度量和特征加权算法为基础．对网络中采集到的各种原始样本参数进行数据预处理，以便为故障诊断提供更加可靠、准确地输入参量，由于安全设备的故障特征具有很强的异构特性，所以首先对特征变量进行分类描述。将变量分为连续型、有序型、标称型、二分型四类23种。之后，对不同类型特征变量，提出Euclid、VDM算法、DVDM度IVDM算法来标称不同样本的距离。最后．综合运用知识规则和模糊理论对四种算法分别赋予不同的权重。通过实验度结果分析。显示加权后DVDM和IVDM算法的故障分类准确度增长10％以上，说明该理论算法具有较高的可靠性和准确度。[著者文摘]
文章出处:
《计算机工程与应用》-2006年42卷34期,22 -1-4,22页
栏目信息:
分 类 号:
文献标识码:
A
文章编号:
1002-8331（2006）34-0001-04
Fault Symptom Handling Algorithm Based on Feature Weighted
CUI Zhong-jie, YAO Shu-ping, TANG Cheng-hua （1.Lab of Computer Network Defense Technology,Beijing Institute of Technology,Beijing 100081,China ; 2.School of Mechanism Engineering,Beijing Institute of Technology,Beijing 100081,China; 3.School of Software Technology, Beijing Institute of Technology, Beijing 100081, China）
Abstract:
In order to avoid security threat in the various networks,the unite network management platform which is composed of many heterogeneous security devices have been application widely. But how to deal with lots of conflicts and faults that arise from security devices have been key point and difficulty of network management. In this paper, distance metric and feature weighted algorithms have been provided for pretreatment of data which are gathered in the network. Because fault features of network security devices have quite heterogeneous character. So the twenty-three feature variables have been partitioned four classes whieh contain continuous attribute,integer attribute,nominal attribute and dimidiate attribute, Then Euclid,VDM,DVDM and IVDM algorithms have been used for represent differ samples＇ distance. Finally,fuzzy theory and knowledge rules have been applied to feature weighted of four algorithms. In the experiment,the fault classification accuracy of the weighted algorithm of DVDM and IVDM increase more than 10 percent. It shows this theory has upper reliability and precision.[著者文摘]
Key words:
fault feature;distance metric algorithm;feature weighted
基金资助:
国家部委科技基础研究项目.
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