The evaluation of data breaches and cybersecurity risks has not yet been formally addressed in modern business systems. There has been a tremendous increase in the generation, usage and consumption of industrial and business data as a result of smart and computational intensive software systems. This has resulted in an increase in the attack surface of these cyber systems. Consequently, there has been a consequent increase in the associated cybersecurity risks. However, no significant studies have been conducted that examine, compare, and evaluate the approaches used by the risk calculators to investigate the data breaches. The development of an efficient cybersecurity solution allows us to mitigate the data breaches threatened by the cybersecurity risks such as cyber-attacks against database storage, processing and management. In this paper, we develop a comprehensive, formal model that estimates the two components of security risks: breach cost and the likelihood of a data breach within 12 months. The data used in this model are taken from the industrial business report, which provides the necessary information collected and the calculators developed by the major organizations in the field. This model integrated with the cybersecurity solution uses consolidated factors that have a significant impact on the data breach risk. We propose mathematical models of how the factors impact the cost and the likelihood. These models allow us to conclude that results obtained through the models mitigate the data breaches in the potential and future business system dynamically.
Reinforcement Learning for Generating Secure Configurations