MATHEMATICAL MODEL FOR CYBERSECURITY RISK ASSESSMENT IN THE ABSENCE OF FINANCIAL DATA ON LOSSES

This article examines the specifics of cybersecurity risk assessment in military information and communication systems (MICS) in wartime conditions, where it is impossible to assess potential financial losses from cyberattacks.A mathematical model for cybersecurity risk assessment in MICS is proposed, based on the Monte Carlo method and considering the specifics of MICS, such as the peculiarities of combined attacks using conventional and cyber weapons in hybrid warfare, and the impossibility of assessing potential financial losses resulting from successful cyberattacks. A mathematical apparatus has been developed to assess the frequency of loss events and system downtime of MICS due to cyberattacks, which allows accounting for uncertainty in estimates and the random nature of cyberattacks. The article provides a detailed review of existing quantitative methods for cybersecurity risk assessment, such as the Bayesian network method, attack tree analysis, quantitative risk assessment (QRA), and the Monte Carlo method. It is shown that the Monte Carlo method has several advantages in the context of risk assessment in MICS, such as flexibility, the ability to account for uncertainty, and the ability to adapt to dynamic changes in the threat landscape. An analysis of the possibility of using various types of statistical distributions in the Monte Carlo simulation process is conducted, and typical scenarios for their application during cybersecurity risk assessment are presented, considering their advantages and disadvantages. Examples of applying the developed model to various scenarios of cyberattacks on MICS are provided, including DDoS attacks, phishing attacks, ransomware attacks, and APT attacks. The proposed approach can be used to make decisions regarding the allocation of resources for the cybersecurity of MICS in wartime. Further research will allow automating risk assessment in MICS, which will enable real-time threat modeling and rapid development of countermeasures, which will significantly increase the resilience of MICS in the context of aggressive warfare in cyberspace.