文献类型：期刊文献

中文题名：基于本体的信息安全漏洞关联分析

英文题名：Information Security Vulnerability Association Analysis Based on Ontology Technology

作者：张雪芹[1];徐金瑜[1];顾春华[1]

机构：[1]华东理工大学信息科学与工程学院,上海200237

年份：2014

卷号：40

期号：1

起止页码：125

中文期刊名：华东理工大学学报（自然科学版）

外文期刊名：Journal of East China University of Science and Technology

收录：CSTPCD;;Scopus;北大核心:【北大核心2011】；CSCD:【CSCD2013_2014】；

语种：中文

中文关键词：信息安全漏洞;领域本体;数据挖掘;管理分析

外文关键词：information security vulnerability; field ontology; data mining; association analysis

摘要：漏洞是引发信息安全问题的重要因素,对漏洞发生情况进行分析预测值得关注。针对信息安全漏洞数据库中的漏洞数据,基于CWE构建信息安全漏洞本体,形成漏洞领域语义基础,采用Apriori关联算法,对软件中漏洞发生情况进行分析预测。在数据挖掘的数据预处理阶段借助该语义知识,通过将低概念层级的漏洞数据泛化至高概念层级,提高项集的支持度,挖掘出隐藏的关联规则;在关联规则评估阶段通过设计基于用户关注度的规则筛选器ADARF和RDARF,实现了根据用户关注度找出符合用户兴趣度的规则;基于CNNVD漏洞库的实验证明了上述方法的有效性。
Vulnerability is an important factor to cause information security problem. It is interesting and significant to predict the occurrence of vulnerability. Aiming at the vulnerability data in security vulnerability database, this paper constructs an information security vulnerability ontology based on CWE （Common Weakness Enumeration）, which will be taken as vulnerability domain semantics. By applying Apriori algorithm, the association relationship among vulnerabilities in software is analyzed and predicted. In the phase of data preprocessing, by means of the vulnerability semantic knowledge, the support of itemsets is improved and the hidden association rules are found by promoting the concept level of vulnerability data from low to high. In the phase of rule evaluation, by designing rule filters, ADARF and RDARF, according to the user attention, the rules matching the interesting of user are obtained. Experiments on the CNNVD vulnerability database demonstrate the effectiveness of the proposed method.