基于距离度量的故障特征处理算法

为了防范网络中存在的多种多样的安全威胁,由大量异构型安全设备所组成的统一管理平台得到了广泛的应用。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。本文提出以距离度量算法为基础,对网络中采集到的各种原始样本参数进行数据预处理,以便为故障检测提供更加可靠、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15种。之后,对不同类型特征变量,提出改进IVDM算法来标称不同样本的距离。最后,通过实验及结果分析,显示IVDM算法较其它算法有更高的准确度和可靠性。

Fault Feature Handling Algorithm Based on Distance Metric

In order to avoid security threat in the various networks, the unite network management platform which is composed of many heterogeneous security devices has been application widely. But how to deal with lots of conflicts and faults that arise from security devices has been key point and difficulty of network management. In this paper, distance metric algorithms have been provided for pretreatment of data which are gathered in the network. Because fault features of network security device have quite heterogeneous character. Fifteen feature variables have been partitioned four classes which contain continuous attribute, integer attribute, nominal attribute and dimidiate attribute. Then the improved IVDM algorithm has been used for represent differ samples' distance. In the experiment, it shows IVDM has upper reliability and precision than other algorithms.