Intelligent data analysis in decision support systems for penetration tests

Abstract

Intelligent data analysis is extensively applied in various fields of technology, including information security. The development of decision support systems (DSSs) for penetration tests is more complicated due to incomplete, undefined, and expandable unstructured data. This article suggests an approach to formalizing information from subject domains, quantitative relevance estimates of object characteristics, and estimates of object similarity.