Abstract
One of the pressing areas that is developing in the field of information security is associated with the use of Honeypots (virtual decoys, online traps), and the selection of criteria for determining the most effective Honeypots and their further classification is an urgent task. The main products that implement virtual decoy technologies are presented. They are often used to study the behavior, approaches and methods that an unauthorized party uses to gain unauthorized access to information system resources. Online hooks can simulate any resource, but more often they look like real production servers and workstations. A number of fairly effective developments are known that are used to solve the problems of detecting attacks on information system resources, which are based on the apparatus of fuzzy sets. They showed the effectiveness of the appropriate mathematical apparatus, the use of which, for example, to formalize the approach to the formation of a set of reference values that will improve the process of determining the most effective Honeypots. For this purpose, many characteristics have been formed (installation and configuration process, usage and support process, data collection, logging level, simulation level, interaction level) that determine the properties of online traps. These characteristics became the basis for developing a method for the formation of standards of linguistic variables for further selection of the most effective Honeypots. The method is based on the formation of a Honeypots set, subsets of characteristics and identifier values of linguistic estimates of the Honeypot characteristics, a base and derived frequency matrix, as well as on the construction of fuzzy terms and reference fuzzy numbers with their visualization. This will allow classifying and selecting the most effective virtual baits in the future.