НЕЙРОНДЫҚ ЖЕЛІЛЕР КӨМЕГІМЕН КОМПЬЮТЕРЛІК ЖЕЛІЛЕРДІҢ АҚПАРАТТЫҚ ҚАУІПСІЗДІГІН ҚАМТАМАСЫЗ ЕТУ
This article discusses the principles of technology for building secure systems. To ensure the security of computer systems, it is proposed to use a security gateway consisting of a set of modules. To improve the performance of the neural network model, preliminary data processing was performed, model parameters were determined, as well as training parameters. In this study, the use of neuronal network analysis to solve problems in selecting the type of neuronal system was chosen. The solution of this analysis is to define the architecture of neuronal systems used to solve multi-layer perspective problems. In this paper, the method of predicting the non-formal dependence of empirical factors is used. In order to improve the functioning of the neuronal system, data processing, model parameters, and parameters of training were conducted. The algorithm of the report, the quality of the model is evaluated. Prepare data as the basis for the success of the report. In this work, the protection of information systems through neurons is provided. According to the analysis, the following types of neurons are favorable: multi-layered perspektron, radial elements with network elements, probable, generalized regression and linear networks. The neuronal line is trained backward. Training is carried out by reducing errors. Disadvantages of neural networks: 1) Ability to involve specialists of the highest category, lack of guarantees for the successful solution of the given report;2) The software does not have a specific direction and can not solve the given problem. In this paper, the method of predicting the non-formal dependence of empirical factors is used.