Adaptive decision support systems for cyber security

Abstract

The subject of the research is the principles and models of adaptive decision support systems in cyber security. The purpose is to develop basic principles and models underlying the operation of adaptive decision support systems in the field of cybersecurity. The methods of research are methods of system analysis, control theory, decision theory, and artificial intelligence. The result of the study. The basic principles and models are proposed, the consideration and use of which in decision support systems will allow the formation of adaptive properties of the described systems. It is shown that the properties of adaptability can be formulated as a learning task. Presents optimization algorithms that underlie learning processes. Conclusion. The combined use of mathematical modeling methods, the theory of adaptation and artificial intelligence methods (training, pattern recognition and problem solving planning) with the corresponding creation of ontologies of cybersecurity systems that ensure the filling of databases, models and knowledge will allow you to implement an effective adaptive decision support system that will be useful a tool for managers at any level at all stages of decision making and implementation. The presented approaches can be used as a basis for building and operating decision support systems, increasing the area of application of such systems due to the formation of their adaptability properties.