Застосування інтелектуальної діагностичної інфраструктури для управління кібербезпекою

Abstract

How use of structural features in the construction of hybrid models allows supporting of models adjustment and adaptation to problem-subject environment was considered in the article. The following features were attributed to structural ones: the type of learning algorithm; kind of activation function; the number of layers of the neural network; type of neurons; way of spreading information in neural networks; method of evaluating and interpreting the results of the neural network; the format of fuzzy inference rules; fuzzification and defuzzification method; way to implement the operations of fuzzy implication and logical operations NOT, AND, OR; kind of used genetic operators and the target functions, etc. We propose to use a neural network approach as a basis for the decision of difficulty tasks using decision-support systems. Its effectiveness can be enhanced by: prior training or adjustment of individual neural modules for solvable problem; incorporation of knowledge about the peculiarities of the domain in the hierarchical (multilayer) neural networks structure; application of basic types of hybrid models in which neural network communicates with other information technologies.