This article aims to analyze the relationship between the threat of ransomware and new effective counteraction principles for law enforcement agencies to utilize. Moreover, it contemplates on how specific behavior of persons can help reduce the threat of being infected with this malicious software. It establishes that certain changes made in society's mentality towards their computer and network systems can significantly reduce the consequent damages of ransomware attacks. The manuscript uses a qualitative research approach and the analysis of variance (ANOVA), including an F-test, which defines major challenges in ransomware. This is the first empirical research piece which uses this type of data and approach for the analysis of current threats in global ransomware security. The article suggests that the main challenge is the systematic growth of ransomware connected to illegal businesses and the inattentive actions of casual users. The research paper proposes the implementation of global ransomware counteraction principles on the base of challenges that are present now and the prospects of rising threats in the future. In addition, the manuscript analyzes the trends of the last 2-years of attacks to find and determine new ways of successfully counteracting it for optimal innovative regional development.

Mafura Uandykova System analysis in economics – 2018: Proceedings of the V International research and practice conference–biennale (21–23 november 2018). —

This article examines innovative methods for developing decision support systems (DSS) in the context of economic development management. The relevance of the study is driven by the need to enhance the efficiency of managing state development programs and optimizing budget resources in the era of digital economic transformation. The authors explore modern methodologies and tools used in DSS development, with particular attention to their application in the economic sphere. The role of the systems approach is considered as a key methodology for creating integrated solutions in public administration and conducting a comprehensive analysis of economic processes.The main goal of the article is to analyze and propose new approaches to DSS development to improve the efficiency of managing state economic programs. The economic aspects and principles of these systems, as well as the main tools and technologies used for their implementation in public administration, are examined. Special attention is given to analyzing the challenges associated with developing DSS to solve economic tasks such as financial forecasting, budget expenditure optimization, and economic risk management.The study highlights the importance of integrating intelligent DSS into the management processes of state economic development programs. Specific tools used in DSS development for economic analysis are examined, and their role in improving economic decision-making processes is explained. The research results include an innovative model for integrating artificial intelligence and big data analysis into DSS has been proposed; methods for improving the accuracy of economic forecasts and enhancing the efficiency of state resource allocation have been identified; a new DSS architecture model for public administration has been developed. The practical significance of the study is that it provides recommendations for implementing innovative DSS in public administration practices for economic development. The proposed approaches aim to enhance the efficiency of budget resource utilization, improve the quality of economic forecasting, and accelerate the processes of making well-founded economic decisions. The proposed approaches are aimed at increasing the efficiency of budgetary funds utilisation, improving the quality of economic forecasting and accelerating the processes of making informed economic decisions. The scope of application: state economic management, strategic planning, optimisation of budgetary resources. Scientific novelty: a comprehensive approach to the creation of SPPR for solving economic problems is proposed, new methods of integration of artificial intelligence and big data analysis are developed.

Байтенова Лаура Маратовна, Уандыкова Мафура Кусмановна Системный анализ в экономике – 2018: сборник трудов V Международной научно-практической конференции –

Уандыкова Мафура Кусмановна Системный анализ в экономике – 2018: сборник трудов V Международной научно-практической конференции – биеннале (21–23 ноября 2018) /