HOST SECURITY ASSESSMENT BASED ON MACHINE LEARNING METHODS: DEVELOPMENT OF MODELS AND ALGORITHMS
DOI:
https://doi.org/10.47390/SPR1342V6SI1Y2026N54Keywords:
cybersecurity, host security, machine learning, anomaly detection, information systems.Abstract
The article proposes a machine learning–based approach for assessing host-level cybersecurity. Traditional signature-based and rule-based protection mechanisms are limited in detecting new and unknown threats. The proposed model analyzes system logs, resource usage metrics, and network activity to evaluate the cybersecurity state of a host. Classification and anomaly detection methods are used to automatically determine the cyber risk level, improving the effectiveness of information security systems.
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