Synthesis of Algorithms for Recognition of Vulnerabilities in Web Resources Using Signatures of Fuzzy Linguistic Features

Abstract

The paper formalizes the problem of fuzzy recognition of vulnerabilities in web resources that is set by a complex reference description in the form of signatures of intervals of the values of fuzzy linguistic features. The reference description and the mathematics of the theory of validation of complex statistical hypotheses were applied to synthesize multi-criteria object recognition algorithms using the minimax decision rule and the Bayesian maximum of a posteriori probability and maximum likelihood criteria.