Mathematical models and algorithms for improving the cybersecurity of network devices

In today's world, network devices are subject to increasingly intense cyber attacks. Traditional approaches to cybersecurity face difficulties in the context of dynamic and highly loaded networks. This article provides an overview and development of mathematical models and algorithms to improve the security of network devices. The methods of graph theory, statistical analysis, and machine learning that can be used to analyze anomalies, model network behavior, and predict potential attacks are being investigated. The research results show that the integration of mathematical methods can significantly improve the accuracy of threat detection and minimize the likelihood of false positives.