Using Probabilistic Models to Assess and Enhance Information Security

Abstract

The article explores the possibilities of using probabilistic models to assess and improve information security. The theoretical foundations of the probabilistic approach are considered, including methods of risk analysis, threat modeling and prediction of potential vulnerabilities. Special attention is paid to the use of models such as Bayesian networks, Markov chains, and Monte Carlo simulations, which allow quantifying the likelihood of incidents and their consequences. The paper presents practical examples of the use of probabilistic models for analyzing the security of information systems, as well as recommendations for their integration into information security management processes.