Method of Linguistic Variable Standards Formation for Honeypot Classification

Abstract

Nowadays, one of the relevant areas that is developing in the field of information security is associated with the use of Honeypot (virtual lures, online traps), and the selection of criteria for determination of the most effective Honeypot and their further classification is an urgent task. There are presented the main products in which virtual lures technology is implemented. Often they are used to study the behavior, approaches and methods that an unauthorized party uses for unauthorized access to information system resources. Online traps can imitate any resource, but more often they look like real production servers and workstations. There are known a number of fairly effective developments that are used to solve the problems of identifying attacks on the information systems resources, which are based on the fuzzy sets apparatus. They showed the effectiveness of using the appropriate mathematical apparatus, the use of which, for example, to formalize the approach for the formation of a set of criteria, will improve the process of determining the most effective Honeypot. For this purpose, there have been proposed criteria that characterize online traps, with the use of which there has been developed a method of linguistic variable standards formation for choosing the most effective Honeypot. The method is based on the formation of a set of Honeypot, subsets of characteristics and identifier values of linguistic estimates of Honeypot characteristics, a base and derivative frequency matrix, as well as on the construction of fuzzy terms and standard fuzzy numbers with their visualization. This will allow further classification and selection of them osteffective virtual lures.