USE OF MATHEMATICAL OPTIMIZATION METHODS TO INCREASE THE EFFICIENCY OF INFORMATION SECURITY SYSTEMS

Abstract

Ensuring information security is a pressing task of our time, as the problem of information risks and finding ways to reduce damage from cyberattacks is becoming increasingly acute. In this paper, we analyzed methods for ensuring information security. Among the economic methods of information protection, information risk insurance occupies an important place. However, such insurance continues to remain a rare occurrence due to insurance companies' concerns about the need to pay policyholders significant amounts of compensation for losses in the event of a mass occurrence of insured events. The use of mathematical modeling methods allows to convincingly prove managers that investing in an information security system contributes to increasing the company's profits, and also, in conditions of limited resources allocated to the development and operation of a cyber defense system, to choose the optimal set of protection tools and, based on a mathematical model, convincingly prove how effective the created information security system is in the fight against the most common threats. The purpose of the work is mathematical modeling of maximizing the effectiveness of information protection tools against unauthorized access with restrictions on the amount of costs. The application of optimization methods to mathematical modeling of quantitative assessments of the quality of functioning of a cybersecurity system allows us to assess the cost-effectiveness of using information protection tools to increase the level of reliability of the information security system. We proposed a mathematical model for maximizing the effectiveness of information protection tools under cost constraints, the use of which can be an argumentative factor for motivating underwriters. Prospects for further research may consist in detailing the criteria for the optimality of creating an enterprise information security system to protect against possible information threats, as well as in studying more complex cases of combined information threats that are interconnected.