A Survey on the State of the Art of Vulnerability Assessment Techniques

Abstract

A suitable vulnerability assessment process improves the overall security of an organization, and therefore, reduces the chances that an attacker could breach the IT system. The detection of vulnerabilities is one of the first steps in software security lifecycle, but in some cases, it is not enough. Understanding how a vulnerability can affect the rest of the system as well as forecasting its exploitability are important issues when assessing its real impact. Under this premise, this paper presents an overview of the state of the art, including different approaches related to the detection, forecasting and propagation of vulnerabilities in software, focusing mainly on Machine Learning and Data Mining techniques.