Abstract

As a result of Russian aggression against Ukraine, some fundamental theses regarding the nature of hybrid military operations will require clarification and even revision. First of all, this refers to the widespread perception of the asymmetric nature of hybrid threats as those used by a weaker opponent against a party with significantly greater military, technological and human potential. This, in turn, requires the use of modern and proven mathematical apparatus, which is capable of processing a large array of various types of data in a short period of time with a given reliability of making management decisions. The object of research is the system of strategic management of national security. The subject of the research is the method of detection and identification of hybrid challenges and threats in the national security management system. In the research, the method of detection and identification of hybrid challenges and threats in the national security management system was developed. The novelty of the research: – a destructive effect on the system of national security management by adding an appropriate correction factor; – the use of an improved procedure of deep learning of the database of the system of detection and identification of hybrid challenges and threats to the national security of the state; – a mechanism for resolving conflicting cases of classification is used due to additional training, adaptation of detectors to the type and intensity of the hybrid challenge and threat to the national security of the state; – the procedure for automatically calculating the detector activation threshold and the universality of the structure of their representation due to the hierarchy and flexibility for the available hardware resources of the detection and identification system. It is advisable to implement the specified method in algorithmic and software while studying the state of the national security system.

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