The article considers artificial neural networks as a means of intelligent data analysis. The relevance of using such networks is due to the active growth of data volumes, which occurs as a result of the automation of various technological processes. The primary methods of data analysis in the field of security science are identified, along with an examination of their respective advantages and disadvantages. As a result, an important conclusion is substantiated: the use of artificial neural networks for the purpose of intelligent analysis of accumulated data is fully justified and expedient, primarily for practical reasons. The areas of application for intelligent data analysis and existing systems are examined. A comparative analysis of the use of neural network architecture within the context of security science conditions is conducted. An approach to a neural network for data selection with the allocation of the relevant stages is proposed. Building on this, a practical demonstration of the simplest recurrent neural network is proposed, with an exploration of the stages involved in this process. An algorithm for constructing the proposed system is outlined. Conclusions are drawn about the promising areas for applying data mining methods.