Development of the space-time structure of the methodology for modeling the behavior of antagonistic agents of the security system

Abstract

The rapid development of computing technologies, the emergence of modern cyber threats with signs of hybridity and synergy puts forward stringent requirements for the economic component of the national security of the state and especially the processes of ensuring the cybersecurity of the functioning of the economy. The cybersecurity industry is trying to keep up with the requirements by introducing new and better technologies and security practices, but such a universal approach is considered insufficient. The study is devoted to solving the objective contradiction between the growing requirements in practice to ensure an appropriate level of cybersecurity of the contours of business processes while increasing the number and technological complexity of cybersecurity threats. At the same time, one should take into account the acquisition by threats of signs of hybridity on the one hand, and imperfection, and sometimes the absence of a methodology for modeling the behavior of interacting agents of security systems. However, this does not allow us to timely predict the future actions of attackers, and as a result, to determine the required level of investment in a security system that will provide the required level of cybersecurity. The paper proposes the Concept of modeling the behavior of interacting agents, the basis of which is a three-level structure of modeling the subjects and business processes of the contours of the organization's functioning and the security system based on modeling the behavior of antagonistic agents. The proposed methodology for modeling the behavior of interacting agents, which is based on the concept of the behavior of antagonistic agents, makes it possible to assess and increase the current level of security by reducing the number of implementation of hybrid threats by 1.76 times, reduces the damage by 1.65 times and increases the time of choosing countermeasures account for 38% reduction in time for online threat identification.