On Improving the System of Statistical Indicators of the Secure Use of Digital Technologies

Abstract

The article presents some results of the study of problems of improving the secure use of digital technologies in the new stage of the development of information and communication technologies (ICT). The relevance is explained by the fact that the use of ICT in the current conditions of the development of the information society and the digital transformation of the economy not only leads to the known positive socio-economic effects but also presupposes the inevitable negative impacts. The objective of protecting the interests of an individual, society, and the state from internal and external information threats is related to the concept of information security. The expansion of its boundaries – from low-level technical measures for the protection of information systems (computer security and cybersecurity) to the strategic management of economic production in this context – has created a new relevant category, digital security, and dictates the expediency of combining these terms into a general concept of «secure use of digital technologies».The author analyzed the existing methodological approaches to the statistical study of the problems under consideration and developed several proposals for improving the corresponding system of statistical indicators. Methods of descriptive statistics, correlation-regression analysis, and machine learning methods (in particular, various variants of classification algorithms based on decision trees) were used in the analysis to achieve this goal.While studying information and methodological sources which are indirectly related to statistical resources (a well-known web platform that brings together researchers in the field of data science and machine learning, Kaggle, was examined), the author analyzed the results of a thematic survey of companies. As a result of modeling the influence of the «secure use of digital technologies» factor on the efficiency of economic activity, it was established that its variation by about a third determines the level of economic efficiency of the company within the presented population. The application of machine learning techniques has resulted in acceptable quality predictive models for classifying companies by economic activity in the same factor context.From a practical point of view, according to the author, the application of the proposed approach to the formation of a system of statistical indicators shall be beneficial for managing processes that ensure the security of the use of digital technologies at the enterprise, region, and country level as a whole.