Development of methodology for modeling the interaction of antagonistic agents in cybersecurity systems - Milov, Oleksandr; Voitko, Alexander; Husarova, Iryna; Domaskin, Oleg; Ivanchenko, Yevheniia; Ivanchenko, Ihor; Korol, Olha; Kots, Hryhorii; Opirskyy, Ivan; Fraze-Frazenko, Oleksii (Eastern-European Journal of Enterprise Technologies, 2019)
The basic concepts that form the basis of integrated modeling of the behavior of antagonistic agents in cybersecurity systems are identified. It is shown that the emphasis is largely on modeling the behavior of one of the cyber conflict parties only. In the case when the interaction of all parties to the conflict is considered, the approaches used are focused on solving particular problems, or they model a simplified situation. A methodology for modeling the interaction of antagonistic agents in cybersecurity systems, focused on the use of a multi-model complex with elements of cognitive modeling, is proposed. For this objective, the main components of cyber conflict are highlighted, the models of which must be developed. Modeling the interaction of antagonistic agents is proposed to be implemented as a simulation of situations. The concept of a situation is formulated and its components are presented. In the proposed methodology, traditional methods and modeling tools are not opposed, but are considered together, thus forming a unified methodological basis for modeling the antagonistic agents’ behavior. In the proposed multi-model complexes, the individual elements and functions of the entities under study are described using various classes of models at a certain level of detail. Coordinated use of various models allows improving the quality of modeling by compensating for the shortcomings of some models by the advantages of others, in particular, reflecting the dynamics of interaction in system-dynamic and agent-based models, which is difficult in classical models of game theory. Multi-model complexes allow stating the concept of «virtual modeling». This concept allows simulation using models of various classes. The choice of a class of models should correspond to the goals and objectives of modeling, the nature and structure of the source data. As a result of research, a methodology is proposed for modeling the interaction of antagonistic agents in cybersecurity systems using methods based on the proposed models of the reflective behavior of antagonistic agents under modern hybrid threats conditions