基于星型网模型的安全漏洞分类

A Vulnerability Taxonomy Based on the Starnet Model

在进行入侵检测技术的研究中,安全漏洞分类是一个重要和必需的过程。然而,现有的漏洞分类在不同程度上都存在一些弊端。为了使分类更加科学、有用,该文提出了一种基于星型网模型的安全漏洞分类。该分类利用星型网的特点,将所有漏洞构造成一个7维数据空间,每一维都有具体的粒度划分,可以利用多维数据模型上的数据挖掘对漏洞进行较全面的多维度的数据分析与知识发现。

In the process of studying intrusion detection technology,the vulnerability taxonomy is an important and necessary process.However,the present vulnerability taxonomies exist some shortcomings in various degrees.To make the taxonomy more scientific and useful ,this paper describes a vulnerability taxonomy based on the startnet model.Using the characters of the starnet,the taxonomy builds all vulnerabilities into a7-D data space with specific granularities in each dimension.Thus,using the data mining on the multi -dimensions data model,the vulnerabilities can be fully analyzed and discovered.