UDC 004.8, 519.7
CONGNITIVE NETWORKS, THEIR PROPERTIES AND APPLICATIONS IN ATTACK
DETECTION AND PREVENTION SYSTEMS
Abstract. Methods of real-time cyberattack detection, based on an algebraic approach, are considered. The method of algebraic matching is used, which is based on the methods of solving behavioral equations and algebraic modeling. At the same time, to increase the efficiency of cyberattack detection and prevention, it is suggested to use the composition of a neural network for the classification of attacks and the method of algebraic matching. This construction is called a cognitive system, whose concept was first formulated in 2005. The properties of the cognitive network, such as double classification and self-learning, are considered, and the technological line for detecting cyberattacks using cognitive networks is presented.
Keywords: artificial intelligence, neuron network, deep machine learning, behaviour algebra, neuro-symbolic approach, algebraic modeling, insertion modelling.
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