Year: 2025
Type: article
Abstract: Introduction. In today's conditions of rapid development of digital technologies and the increase in the number of cyberattacks, the issue of effective protection of operating systems is becoming particularly relevant. Traditional information security tools are often unable to respond in a timely manner to the latest types of threats that are constantly evolving and becoming more complex. One of the key problems remains the insufficient effectiveness of methods for predicting cyberattacks, which does not allow for timely detection of potential vectors of interference in systems. At the same time, modern statistical analytics opens up new opportunities for developing models that can determine the probability of an attack even before it is actually carried out. One of such methods is the use of the Pearson correlation coefficient to identify patterns between system activity and the probability of cyber incidents. However, in practice, research in this area remains fragmented, and a systematic approach to modeling protection - taking into account statisticaldependencies between security parameters - is still developed. Thus, the arises a need to develop a comprehensive model for protecting operating systems from cyberattacks. This model should be based on the analysis of correlations between the system’s behavioral characteristics and indicators of a potential threat, using the Pearson criterion as a tool for identifying significant dependencies.Purpose. The purpose of this article is to develop and substantiate a model of an action plan for protecting operating systems from cyberattacks. The proposed model identifies correlations between system performance parameters and threat indicators using the Pearson criterion, and applies the results to predict the probability of attacks and enhance anomaly detection systems in cyberspace.Results. The article presents the results of a study that modelled the protection of operating systems against cyberattacks. The study used the Pearson criterion to identify statistically significant relationships between quantitative cyberthreat cases against different types of operating system.A cybersecurity action plan for Windows and Linux operating systems was modelled based on the results obtained, taking into account their specifics and equivalent vulnerability to cyberattacks.The key areas of protection are outlined, including system updates, access control, monitoring, network security, redundancy and staff training.Conclusion. The proposed modelling, based on the Pearson criterion, enables the effective detection of statistical patterns preceding the implementation of cyberattacks on operating systems.The use of such an approach increases the level of preventive protection and contributes to the timely detection ofpotential threats.
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $16
OpenAlex ID: W4411705292