درخت حوزه‌های تخصصی

As a result of the introduction of digital technologies in all spheres of society, various latest technologically conditioned risks and threats have become various. It requires the formation and implementation of a legal mechanism for further development and operation of the system ensuring information security, taking into account the effects of digitalization and transformation of society. The purpose of this study is development of scientifically substantiated proposals and recommendations for implementation legal mechanisms for information security in the context of digitalization. The relevance of this study is due to the needlegal regulation of relations in the information sphere, formation of a system of protection and counteraction to cybercrime. To achieve the goal of the study, methodological principles and approaches of legal science were used. The results of the analysis showed that the most significant mutual influence is demonstrated by a group of indicators of the state's institutional capacity and a group of indicators of the digital capacity of the national economy and cybersecurity. This study substantiates the main directions of accelerating the optimization of the institutional system of cybersecurity in Ukraine, which provides for two key areas: legal and organizational. The legal mechanisms include further improvement and harmonization of the regulatory framework, the formation of relevant legal norms, state policy in the field of information security. The organizational measures are aimed at improving the efficiency of responsible institutional structures - the subjects of cybersecurity - by increasing their capabilities, eliminating duplication in the exercise of their powers, taking into account the best practices of international and European experience. The core of the integrated information security system is the National Cyber Security Coordination Center.

The most common starting point for investors when buying a stock is to look at the trend of price changes. In recent years, different models have been used to predict stock prices by researchers, and since artificial intelligence techniques, including neural networks, genetic algorithms and fuzzy logic, have achieved successful re-sults in solving complex problems; in this regard, more exploitation Are. In this research, the prediction of stock prices of companies accepted in the Tehran Stock Exchange using artificial intelligence algorithm (non-sensory-parametric support vector regression algorithm in linear and nonlinear mode) has been investigated. The results of the research show that the PINSVR algorithm in nonlinear mode has been able to predict the stock price over the years, rather than linear mode.