An Intelligent Model for Vulnerability Analysis Using Attack Graph

Constructing attack graph is an important approach to analyze vulnerabilities. Although automated generating attack graph have been proposed to discover the possible attack graphs efficiently, they still require manual effort and expert knowledge to describe the attack templates before the computerized model checking procedure can be performed. Moreover, without considering the configuration changes and attackers´ goals in large complicated network, many attack graphs generated may be impractical in real attack. In this paper, we proposed an intelligent model for vulnerability analysis, taking into account of the attackers´ goals and configuration information, which automatically generates attack graphs by defining a series of prolog facts and rules.